2019 한국수리생물학회 연례 학술대회 · poster session mathematical modeling of the...
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2019 한국수리생물학회 연례 학술대회2019 Annual Conference of Korean Society for Mathematical Biology (KSMB '19)
초 록 집Program & Abstracts
•일시 : 2019년 6월 20일(목) ~ 6월 22일(토)
•장소 : 서귀포 칼호텔 및 제주대 서귀포연수원
| 주최 | 한국수리생물학회
| 주관 | 부산대학교 산업수학센터
한국수리생물학회
| 후원 | 부산대학교 산업수학센터
학회 연락처 [email protected] 학회 홈페이지 http://www.ksmb.org
2019 한국수리생물학회 2 2019.06.20(목) - 6.22(토)
2019 한국수리생물학회 학술대회 조직위원회
조직위원장 김용국 경북대학교, 국가수리과학연구소
김현민 부산대학교
조직위원 이창형 UNIST
정일효 부산대학교
김양진 건국대학교
정석근 제주대학교
2019 한국수리생물학회 학술대회 일정표 6월 20일-22일서귀포칼호텔 및
제주대 서귀포연수원
날짜 시간 일정/장소 강연장 Lobby
제주대 서귀포연수원 세미나룸
15:30 ~ Registration Registration
Slot 1 16:00-18:00 SessionDiscussion and Networking:국내 수리생물학 분야의 비전과
KSMB의 역할
서귀포 칼호텔 크리스탈 로즈 사파이어 Lobby
08:30 ~ Registration Registration
Slot 2 09:00-10:40 Parallel Sessions
Session A1고병원성조류인플루엔자 방역 분
야의 수리통계학 적용 사례(좌장: 윤하정)
Session A2Transmission dynamics of
Tuberculosis disease(좌장: 김소영)
Session A3Mathematical model and
optimization(좌장: 김상일)
10:40-10:50 Coffee Break Coffee Break
10:50-11:00 Opening CeremonyOpening Remarks
(KSMB 회장)
Slot 3 11:00-11:50 Plenary Lecture
Plenary Lecture IOptimization of oncolytic
adenovirus-mediated antitumorimmune efficacy(Speaker: 윤채옥)
12:00-13:00 Lunch 서귀포칼호텔내 식당
Slot 4 13:00-13:50 Poster Session Poster Session
Slot 5 13:50-15:30 Parallel SessionsSession B1
Cancer and cellular mechanism(좌장: 김양진)
Session B2A practical approach to retrievaland analysis of biomedical data
(좌장: 박용근)
Session B3신약개발 모델링(좌장: 윤강준)
15:30-15:40 Coffee Break Coffee Break
Slot 6 15:40-17:20 Parallel Sessions
Session C1Mathematics and statistics on
the spread of infectiousdiseases
(좌장: 손우식)
Session C2Research on mathematicalmodeling of human body
(좌장: 이완호)
Session C3Mathematical modeling ofbiological systems and its
applications(좌장: 윤민)
17:20-17:30 Coffee Break Coffee Break
Slot 7 17:30-18:20 Plenary Lecture
Plenary Lecture IIPrecision cancer medicine and
mathematics(Speaker: 박용근)
18:20-18:30 Poster Award Poster Award (KSMB 회장)
18:30-20:30 Banquet 서귀포칼호텔 연회장
서귀포 칼호텔 크리스탈 로즈 사파이어
09:30 ~ Registration Registration
Slot 9 10:00-12:00 Parallel Sessions
Session D1Ecological modelling:
monitoring, assessment, andmanagement(좌장: 박영석)
Session D2Mathematical approaches to
epidemic models andinteracting systems
(좌장: 이효정)
12:00 Closing
6월 20일(목)
6월 21일(금)
Slot 8
6월 22일(토)
2019 한국수리생물학회 4 2019.06.20(목) - 6.22(토)
2019 한국수리생물학회 5 2019.06.20(목) - 6.22(토)
2019 KSMB 학술대회 일정
6월 20일 (목) [ *장소 : 제주대 서귀포연수원 ]
15:30- Registration
16:00-18:00
Session : Discussion and Networking
토론 주제: 국내 수리생물학 분야의 비전과 KSMB의 역할
2019 한국수리생물학회 6 2019.06.20(목) - 6.22(토)
6월 21일 (금) [ *장소 : 서귀포 칼호텔 ]
09:00-10:40 Session A1: 고병원성조류인플루엔자 방역 분야의 수리통계학
적용 사례 (좌장: 윤하정)
① 빅데이터를 활용한 가축사육농장 재난형 동물질병 예방을 위한 선제적 방역조치 사례
(윤하정)
② Risk assessment of transmission for poultry farms from the antigen detection of
HPAI (조기필)
③ 설명가능 머신러닝(MLI) 방법론을 활용한 HPAI 발생 농가 예측 모형 개발에 관하여
(송유한)
④ Development of a livestock disease control strategies decision making support
system using the KAHIS (김으뜸)
⑤ 다이내믹 네트워크 분석을 통한 농장간 고병원성조류인플루엔자 전파 위험도 분석
(유대성)
⑥ Spatial Epidemiology of highly pathogenic avian influenza H5N6 in Gyeonggi
Province, Korea using Bayesian geostatistical model (임준식)
⑦ 병원체의 유전정보를 통한 병원체 전파의 재구성: 세계 말 인플루엔자 바이러스 전파
에 Phylogeography의 활용 (이규영)
09:00-10:40
Session A2: Transmission dynamics of Tuberculosis disease
(좌장: 김소영)
① Basic Epidemiology of Tuberculosis needed for Mathematical Modelling of Tuberculosis
(Hee Jin Kim)
② Mathematical Modeling of Tuberculosis in the Republic of Korea (Sunhwa Choi)
③ Mathematical Modeling of Tuberculosis transmission in the high Tuberculosis burden
countries (Soyoung Kim)
09:00-10:40
Session A3: Mathematical model and optimization
(좌장: 김상일)
① Optimal Constant for Generalized Diagonal Update Method (Young-jin Kim)
② Optimal Control Strategies for Common Squid(Todarodes Pacificus) in South Korea
(Geunsoo Jang)
③ An optimal route recommendation system for ships based on A* search algorithm - part1&2
(Seungheon Yi & Taehyeong Kim)
2019 한국수리생물학회 7 2019.06.20(목) - 6.22(토)
10:40-10:50 Coffee Break
10:50-11:00
Opening Remarks
(KSMB 회장)
11:00-11:50 Plenary Lecture I: Optimization of oncolytic adenovirus-
mediated antitumor immune efficacy (Speaker: 윤채옥)
12:00-13:00 Lunch (서귀포 칼호텔 식당)
13:00-13:50
Poster Session
Mathematical modeling of the 2016-2017 the Republic of Korea HPAI epidemic and
the optimal strategies considering spatial heterogeneity (Youngsuk Ko)
Role of OCT1 in regulation of miR-451-LKB1-AMPK-OCT1-mTOR core signaling
network and cell invasion in glioblastoma (Donggu Lee)
Synergistic Effects of Bortezomib-OV Therapy and Anti-Invasive Strategies in
Glioblastoma: A Mathematical Model (Junho Lee)
Strong competition model with non-uniform dispersal in a heterogeneous
environment (Wonhyung Choi)
The effect of dispersal toward fitness for predators with predation-induced dispersal
(Kwangjoong Kim)
Blood Flow in Catheterized Artrey: Numerical Study (Shama Javeed)
NASH(Nonalcoholic steatohepatitis) control: Nrf1 and microRNA-378 form a double
negative feedback model (Sieun Lee)
Effects of climate change on malaria transmission dynamics (Yongin Choi)
2019 한국수리생물학회 8 2019.06.20(목) - 6.22(토)
13:50-15:30 Session B1: Cancer and cellular mechanism (좌장: 김양진)
① Overview: Recent advances in tumor growth modeling (Yangjin Kim)
② System identification on mechano-chemical epithelial sheet dynamics (Honda Naoki)
③ The role of Notch signaling in tumor microenvironment (Kyung-Hee Chun)
④ Derivation of mathematical modeling for the diffusion and penetration of
monoclonal antibody delivery into tumor (Hyeongi Kim)
⑤ Control Strategies for Glioblastoma Therapy (Aurelio A. de los Reyes V)
13:50-15:30 Session B2: A practical approach to retrieval and analysis of
biomedical data (좌장: 박용근)
① MicroRNAs associated with vascular invasion in hepatocellular carcinoma and their
prognostic significance: an analysis using publicly available genomic databases
(YongKeun Park)
② Prediction of disease-free survival via gene-DNA methylation signature model and
machine learning model in stage I-II colorectal cancer patient (Min Geun Park)
③ Development of artificial intelligence models for early warning system in intensive
care unit (Dukyong Yoon)
④ Complex Brain Network Analysis: An Introduction (Bumhee Park)
13:50-15:30 Session B3: 신약개발 모델링 (좌장: 윤강준)
① Prediction of Kinase-Inhibitor Activity (김병천)
② Global very weak solution for a nonlinear population model with spatial
heterogeneity (Yong Sul Won)
③ Monolithic Image Decomposition: Structure-Texture Extraction Method
(Gangjoon Yonn)
15:30-15:40 Coffee Break
15:40-17:20 Session C1: Mathematics and statistics on the spread of
infectious diseases (좌장: 손우식)
① Interplay of mathematical epidemiology and economic considerations (Eunha shim)
② Spatial heterogeneity and control measures during avian influenza epidemic 2016-
2017 in Korea (Jonggul Lee)
③ 응급실 기반 감염병 자료 자동수집 및 분석시스템 구축 전략연구 (김선월)
④ The characteristics of regional and age-group-specific spread of influenza in Korea
(Woo-Sik Son)
2019 한국수리생물학회 9 2019.06.20(목) - 6.22(토)
15:40-17:20 Session C2: Research on mathematical modeling of human
body (좌장: 이완호)
① Prediction of Cardiac Function using Patient’s Blood Pressure Data (Wanho Lee)
② Bacterial swimmers propelled by helical flagella (Sookkyung Lim)
③ Predicting the Hemodynamics at the Microvascular-Network Level with Experimental
Validation (Tae-Rin Lee)
④ Hypothesis on fingerprint pattern formation using mathematical modeling
(Seunggyu Lee)
15:40-17:20 Session C3: Mathematical modeling of biological systems and
its applications (좌장: 윤민)
① Modeling of cell to cell infection in a growing plaque to quantify role of amino acid
mutations in GP of filovirus (Kwangsu Kim)
② Complex synchronization of a ring-structured network of FitzHugh-Nagumo neurons
with single- and dual- state gap junctions under ionic gates and external electrical
disturbance (Malik Muhammad Ibrahim)
③ A mathematical model for the management of Plasmodium vivax malaria endemic
in South Korea with realistic distributions of incubation and relapse (Sungchan Kim)
④ Strategic dynamics analysis of smoking and smoking substitute through
evolutionary game theory (Jae Hun Jung)
17:20-17:30 Coffee Break
17:30-18:20
Plenary Lecture II: Precision cancer medicine and mathematics
(Speaker: 박용근)
18:20-18:30
Poster Award
(KSMB 회장)
18:30-20:30 Banquet (서귀포 칼호텔 연회장)
2019 한국수리생물학회 10 2019.06.20(목) - 6.22(토)
6월 22일 (토) [ *장소 : 서귀포 칼호텔 ]
10:00-12:00 Session D1: Ecological modeling: monitoring, assessment, and
management for ecosystems (좌장: 박영석)
① Development of a Predictive Bayesian network Model for Application to the Alert
System for Cyanobacterial Blooms of South Korea (YoonKyung Cha)
② Evolvement of a length-based model: its application to Korean chub
mackerel(Scomber japonicus) stock (Jinwoo Gim)
③ Application of a Bayesian state-space production model to assessment of Korean
chub mackerel(Scomber japonicus) stock (Yuri Jung)
④ Spatial Patterns of Benthic Macroinvertebrate Commuinites (KyoungEun Lee)
⑤ Evaluating the status of freshwater biodiversity in upper-middle basin in Nakdong
River, Korea (Mi-Jung Bae)
⑥ 자료 기반 모델을 이용한 담수어류 출현 특성 분석 및 예측 (이대성)
⑦ Biological Integrity and Ecosystem Regime Shift (Dong-Kyun Kim)
10:00-12:00 Session D2: Mathematical approaches to epidemic models and
interacting systems (좌장: 이효정)
① Estimating the congenital rubella syndrome accounting for asymptomatic
infection using serological data in Japan (Hyojung Lee)
② Feedback control problem of an SIR epidemic model based on the Hamilton-
Jacobi-Bellman equation (Yoon-gu Hwang)
③ Optimization on PDE Model of the Multiple-coated Oncolytic Viruses and
Cancer Cells (Taeyong Lee)
④ Effect of Cooperation in Two-Species Microbial System (Jin-Hyeon Kim)
⑤ A Mixed Effect Model for HIV Dynamics (Yunjeong Lee)
12:00- Closing
2019 한국수리생물학회 11 2019.06.20(목) - 6.22(토)
Plenary Lectures
2019 한국수리생물학회 12 2019.06.20(목) - 6.22(토)
2019 한국수리생물학회 13 2019.06.20(목) - 6.22(토)
Plenary Lecture I
Optimization of oncolytic adenovirus-mediated antitumor immune efficacy
Chae-Ok Yun
Department of Bioengineering, College of Engineering, Hanyang University
Oncolytic adenovirus (Ad), which selectively replicate in cancer, is emerging as a promising new
modality for the treatment of cancer and it has several advantageous attributes over non-replicating Ads.
Oncolytic Ad possesses an inherent ability to multiply, lyse infected cancer cells, and spread to
surrounding cells. Although oncolytic adenovirus is capable of inducing antitumor immune response
even in the absence of therapeutic transgenes, arming the oncolytic Ad with immune stimulatory
transgenes (cytokines, chemokines, and ligands) significantly improves the virus’ ability to induce
robust immune response against the tumor.
Currently, intratumoral injection of an oncolytic Ad remains the conventional administration route in
clinical trials. Nonetheless, the locally administered Ad disseminates to the surrounding nontarget
tissues and has short biological activity due to immunogenicity of Ad, which inadvertently promotes
rapid clearance and insufficient intratumoral retainment of therapeutics. To address these limitations,
we developed biocompatible and biodegradable hydrogels to enhance the therapeutic efficacy of
oncolytic Ads. A hydrogel-based intratumoral delivery of oncolytic Ads prolonged intratumoral virion
retention and lowered nonspecific shedding to normal tissues. Notably, hydrogel systems attenuated
Ad-associated antiviral immune response, while preserving the viruses’ ability to induce robust
antitumor immune response. Importantly, a single hydrogel matrix enabled efficient co-delivery of both
oncolytic Ad and therapeutic dendritic cells, resulting in superior antitumor immune response and tumor
growth control than combination of these treatments in the absence of hydrogel. Collectively, hydrogel-
based delivery of oncolytic Ad can prime immunologically unresponsive ‘cold’ tumor
microenvironment to a ‘hot’ environment that potentiats antitumor immune response by the virus as
well as other immunotherapeutics.
REFERENCES
1) Adrianne L. Jenner, Chae-Ok Yun, Arum Yoon, Adelle C. F. Coster & Peter S. Kim, Modeling combined virotherapy and immunotherapy:
strengthening the antitumour immune response mediated by IL-12 and GM-CSF expression, Letters in Biomathmatics, 5(S1), S99-S116, 2018.
2) Adrianne Jenner, Chae-Ok Yun, Arum Yoon, Peter S. Kim, Adelle C.F. Coster, Modeling heterogeneity in viral-tumour dynamics: the effects
of gene-attenuation on viral characteristics, Journal of Theoretical Biology, 454:41-52, 2018.
3) Adrianne Jenner, Chae-Ok Yun, Peter S Kim, Adelle C.F. Coster, Mathematical modelling of the interaction between cancer cells and an
oncolytic virus: insights into the effects of treatment protocols, Bulletin of Mathematical Biology, 80(6):1615-1629, 2018.
4) Jin Woo Hong and Chae-Ok Yun, Emergence of Ad-mediated combination therapy against cancer: What to expect?, Current Cancer Drug
Target, 18(2):139-152, 2018.
5) Bo-Kyeong Jung, Eonju Oh, inWoo Hong, Yunki Lee, Ki Dong Park, and Chae-Ok Yun, A hydrogel matrix prolongs persistence and promotes specific localization of an oncolytic adenovirus in a tumor by restricting nonspecific shedding and an antiviral immune response,
Biomaterials, 147:26-38, 2017.
6) Eonju Oh, Jung-Eun Oh, JinWoo Hong, YoonHo Chung, Yunki Lee, Ki Dong Park, Sungwan Kim, Chae-Ok Yun, Optimized biodegradable
polymeric reservoir-mediated local and sustained co-delivery of dendritic cells and oncolytic adenovirus co-expressing IL-12 and GM-CSF
for cancer immunotherapy, Journal of Controlled Release, 259:115-127, 2017.
2019 한국수리생물학회 14 2019.06.20(목) - 6.22(토)
Plenary Lecture II
Precision Cancer Medicine and Mathematics
Yongkeun Park Catholic Kwandong University College of Medicine
Department of Surgery, CKU International St. Mary’s Hospital
When patients are diagnosed with cancer, they usually receive the same treatment as others who have
the same stage of cancer. It works for some patients but not for many others. Because we don’t fully
understand how cancers develop and what the most important factor is in their progression, our efforts
to treat these diseases are often imprecise, unpredictable and ineffective. In addition, there is still no
established treatment strategy for some types of cancers.
Precision medicine, also called personalized medicine, is expected to make ways that allow doctors to
select the right treatments that are most likely to help patients based on their specific conditions. [1]
The ultimate goal of it is to deliver the right treatment to the right person at the right time. [2] These
attempts are based on the belief that cancer treatment can be tailored to the genetic background of each
patient’s cancer cells, to the status of the tumor itself, and to patient’s physiologic status. The idea of
precision medicine is not new, but recent advances in science and technology have helped speed up the
pace of this area of research. [1] Nowadays, we can easily get big data from clinical or molecular biology
field. However, a more innovative method is also needed to analyze this data and obtain practical
conclusions. Quantitative, patient-specific information which is integrated via algorithmic analyses can
aid patient stratification, monitoring and treatment design. [2] This is where mathematics comes into
play a very important role.
Mathematics is not new in medicine. Statistics have long been used to describe the result in
observational studies and clinical trials. The application of mathematical models in medicine also has a
long history, and increasing attention has been paid to it, being expected to give a clue of dissecting
complex disease mechanism. Theoretical models expressed mathematical equations can describe
mechanisms of diseases as a systematic approach. It aims to identify critical parameters or to show how
changes in parameter values affect the mechanism of a disease. [3,4] We hope it will not only provide
us with a clue to understanding the disease but will also help us make an accurate decision in health
care.
In this talk, it will be presented how mathematics can aid us in making clinical decisions for patients
with cancer and in understanding the molecular mechanism of cancer development.
REFERENCES [1] National Cancer Institute (https://www.cancer.gov/about-cancer/treatment/types/precision-medicine)
[2] Colijn C et al. Towards Precision Healthcare: context and mathematical challenges. Frontiers in Physiology, 8,136 (2017)
[3] Glynn P et al. Mathematical modeling of physiological systems: an essential tool for discovery. Life Sci 111,1-5 (2014)
[4] Geman D et al. An argument for mechanism-based statistical inference in cancer. Hum Genet 134,479-495 (2015)
2019 한국수리생물학회 15 2019.06.20(목) - 6.22(토)
Special Sessions
2019 한국수리생물학회 16 2019.06.20(목) - 6.22(토)
2019 한국수리생물학회 17 2019.06.20(목) - 6.22(토)
Session A1
고병원성조류인플루엔자 방역 분야의
수리통계학 적용 사례
Organizer: 윤하정 (농림축산검역본부 역학조사과)
Date/Time: 6월 21일(금) 09:00
Speakers:
1. 윤하정 (농림축산검역본부 역학조사과)
2. 조기필 (부산대학교 산업수학센터)
3. 송유한 (한국외국어대학교)
4. 김으뜸 (강원대학교 동물의학종합연구소)
5. 유대성 (농림축산검역본부 역학조사과)
6. 임준식 (농림축산검역본부 역학조사과)
7. 이규영 (University of California, Davis)
2019 한국수리생물학회 18 2019.06.20(목) - 6.22(토)
빅데이터를 활용한 가축사육농장 재난형 동물질병 예방을
위한 선제적 방역조치 사례
윤하정, 이광녕, 정충식, 유대성, 홍성근, 이일섭, 김경숙, 손한모
농림축산검역본부 역학조사과
해외 가축전염병의 생물학적 위협으로부터 국민을 안전하게, 생산자를 풍요롭게 하는 것이 주요
미션인 농림축산검역본부에서 동물방역은 동물검역, 동식물위생연구와 더불어 가장 중요한 업무
이다. 동물방역은 구제역, 조류인플루엔자 등 주요 가축전염병 발생을 최소화하여 근절 기반을
조성하는 것에 중점을 두고 추진된다. 동물방역에 다양한 역학적 기법이 적용되며, 최근 수년간
빅데이터 및 인공지능에 기반한 접근법이 크게 각광을 받게 되었다. 이 세션에서는 빅데이터를
활용한 선제적 방역사례 등 검역본부의 재난형 동물질병 방역조치 의사결정 지원시스템과 관련된
역학연구에 대하여 소개한다. 아울러 국가 동물방역 시스템에 축적되는 데이터의 효과적 활용방
안에 대하여 논의하고자 한다.
REFERENCES
[1] Mooney, S.J. & Pejaver, V. (2018). Big Data in Public Health: Terminology, Machine Learning, and Privacy.
Annu Rev Public Health, (39):95-112.
2019 한국수리생물학회 19 2019.06.20(목) - 6.22(토)
Risk assessment of transmission for poultry farms from the
antigen detection of HPAI
Giphil Cho1), Seong-Uk Nam1), Hachung Yoon2), Kwang-Nyeong Lee2), Han-Mo Son2),
and Hyun-Min Kim1)
1) Finance Fishery Manufacture Industrial Mathematics Center on Big Data,
Pusan National University
2) Veterinary Epidemiology Division, Animal and Plant Quarantine Agency
HPAI(Highly Pathogenic Avian Influenza) is an epidemic of high virulence among AI(Avian
Influenza), which can cause some problems, such as the enormous losses in economics and the
possibility to infect the human being. We propose a stochastic model to estimate risk
assessment of HPAI transmission for poultry farms. In our model, we considered migration of
livestock transport vehicle movement and wild birds as factors influencing the spread of HPAI.
To simulate the risk probability, the initial probability of infection was estimated stochastically
for farms and vehicles that had passed for 5 days within 3km of the HPAI antigen detection.
Infection of farms was estimated stochastically for periods of one day, and then modeled
through days using information of livestock transport vehicle and wild birds movement and
considered farm density on secondary spread. As a result, we can propose an abatement strategy
based on the risk probability calculated by our model.
REFERENCES
[1] Wang, R. H., Jin, Z., Liu, Q. X., van de Koppel, J., & Alonso, D. (2012). A simple stochastic model with
environmental transmission explains multi-year periodicity in outbreaks of avian flu. PLoS One, 7(2), e28873.
2019 한국수리생물학회 20 2019.06.20(목) - 6.22(토)
설명가능 머신러닝(MLI) 방법론을 활용한
HPAI 발생 농가 예측 모형 개발에 관하여a)
최대우1), 송유한*1), 주재윤1), 한예지1), 이광녕2), 유대성2), 손한모2)
1) 한국외국어대학교 통계학과
2) 농림축산검역본부 역학조사과
고병원성조류인플루엔자(HPAI)는 세계동물보건기구에서도 위험도가 높아 관리대상 질병으로 지
정하고 있다. HPAI 국내 유입 시 가금류의 살 처분 등의 문제는 농가뿐 아니라 사회에 많은 피해
를 준다. 본 연구에서는 농가정보, 등록 차량이동 정보 및 날씨, 철새도래지, 일반 GIS 정보 등을
총 망라한 빅데이터를 활용하여 HPAI 발생 농가들을 예측하고자 한다.
우선 농장을 중심으로 그 주변 및 그와 관련된 시계열적 흐름과 변화를 예측 시점에서 활용할
수 있는 데이터 마트를 구축한다. 이러한 데이터 마트를 이용하여 여러 모델링 기법을 적용하여
예측 모형을 개발하되, 설명가능 머신러닝(MLI, Machine Learning Interpretability) 방법을 활용하여
발생 주요원인을 파악을 시도 중이다.
본 발표에서는 검역본부 내의 빅데이터 시스템 및 다양한 외부 자료들을 활용한 예측용 데이터
마트 구성 및 생성 과정에 대한 설명을 진행하며, 예측 모형에 대한 설명으로 MLI 방법을 활용하
여 HPAI 발생 농가 예측 모형 개발에 대한 부분에 대해서 소개하겠다.
주요 용어 : 다이내믹 데이터 마트(Dynamic Data Mart), MLI(Machine Learning Interpretability)
a) 이 연구는 2019년도 정부(과학기술정보통신부)의 재원으로 정보통신기술진흥센터의 지원을 받아 수
행된 연구임 (2018-0-00430, 인공지능기술을 활용한 고병원성 조류인플루엔자 국내 유입, 발생 조기
감지 및 확산 대응 시스템 개발)
2019 한국수리생물학회 21 2019.06.20(목) - 6.22(토)
Development of a livestock disease control strategies decision
making support system using the KAHIS
김으뜸
강원대학교 수의과대학 동물의학종합연구소
본 연구는 재난형 가축전염병인 구제역 혹은 고병원성 조류인플루엔자 등의 관리를 위한방역정
책 결정에 활용할 수 있는 의사결정지원시스템을 구축하기 위해 수행되었다. 본 의사결정시스템
은 국가동물방역통합시스템(Korea Animal Health Integrated System)을 포함한 공공기관 데이터를 기반
으로 재난형 가축전염병 전파 위험요인 및 위험지역 분석을 수행할 수 있도록 설계되었다. 전파
위험요인 분석은 로지스틱 회귀모형을 이용한 분석과 머신러닝기법 중 하나인 boosted regression
trees(BRT)모형을 이용한 방법을 사용자가 선택하여 사용할 수 있도록 설계하였다. 사용자는
KAHIS 내 축산시설 정보 및 축산차량이동정보는 물론 기온 등과 같은 가축전염병 관련 요인을
데이터셋(dataset)화 하여 분석시스템에 업로드한 뒤 위험요인분석을 실시한다. 위험요인 분석 결
과(로지스틱 회귀분석의 경우 독립변수별 오즈비(odds ratio) 그리고 BRT분석의 경우 상대적 기여
도(relative contribution))를 계수로 설정하여 전국 시군별 전파 고위험지역 추정 및 결과 시각화를
실시할 수 있도록 설계하였다. 본 재난형 가축전염병 의사결정지원시스템을 통한 질병전파 위험
요인 및 전파 고위험지역 관리를 통해 질병발생으로 이한 사회/경제적 손실 감소를 기대할 수 있
으며, 인적 혹은 물적 방역자원의 효율적 활용을 도모할 수 있을 것으로 사료된다. 본 연구는 농
림식품기술기획평가원의 지원으로 수행하였다(과제번호: 318034-3).
2019 한국수리생물학회 22 2019.06.20(목) - 6.22(토)
다이내믹 네트워크 분석을 통한 농장간
고병원성조류인플루엔자 전파 위험도 분석
(Risk assessment for Inter-farm Transmission of Highly
Pathogenic Avian Influenza by dynamic network analysis)
Dae-sung Yoo1,2, Kwang-Nyeong Lee1, Hachung Yoon1, Seong-Keun Hong1, Han-Mo Son1
1 Veterinary Epidemiology Division, Animal and Plant Quarantine Agency, Gimcheon, Gyeongsangbuk-do,
Republic of Korea
2 Department of Public Health, Korea University Graduate School, Seoul, Republic of Korea
2016년 11월 이후 2017년 3월까지 국내 산란계 농장에서 전무후무한 대규모 고병원성조류인플루
엔자(Highly Pathogenic Avian Influenza, HPAI) 발생하여 국내 가금농장 산업 뿐만 아니라 계란 값의
상승으로 인해 국민들의 먹거리 확보에도 큰 피해를 끼쳤다. 이러한 산란계 농장의 대규모 HPAI
발생은 역학조사가 결과 농장간 차량 및 사람에 의한 전파에 가능성이 높은 것으로 파악되었다.
이에 HPAI 발생 산란계 농장 116개소에 대해 축산차량에 출입에 의한 일자별 네트워크를 파악하
여, 다이내믹 네트워크 분석 방법 중 하나인 Stochastic Actor-Oriented Model 을 이용하여 시간별 농
장의 연결의 변화 (network evolution)에 영향을 미치는 주요 인자를 파악하고 이를 통해 농장간
HPAI 전파 시 중요하게 작용한 위험요인을 파악하였다.
REFERENCES
[1] Cox R, Revie CW, Hurnik D, Sanchez J. Use of Bayesian Belief Network techniques to explore the interaction
of biosecurity practices on the probability of porcine disease occurrence in Canada. Prev Vet Med., 131:20-30.
(2016)
[2] Farine DR. A guide to null models for animal social network analysis. Methods in ecology and evolution. ,
1309-20, (2017)
2019 한국수리생물학회 23 2019.06.20(목) - 6.22(토)
Spatial Epidemiology of highly pathogenic avian influenza H5N6 in
Gyeonggi Province, Korea using Bayesian geostatistical model
Jun-Sik Lim1, 2,3, Ricardo Soares Magalhaes3, 4, Kwang-Nyeong Lee3, Han-Mo Son3, and Sung-il Cho1
1Veterinary Epidemiology Division, Animal and Plant Quarantine Agency, Gimcheon, Republic of Korea; 2Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea;
3UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Gatton,
Australia; 4Children’s Health and Environment Program, Child Health Research Centre, The University of
Queensland, Brisbane, Australia;
3Veterinary Epidemiology Division, Animal and Plant Quarantine Agency
In the Republic of Korea, during 2016-2017, about 300 affected farms of highly pathogenic avian
influenza (HPAI) H5N6 were reported. Of them, 123 cases occurred in the Gyeonggi Province. However,
to the author’s best knowledge, quantitative analyses that can contribute to the risk-based surveillance
systems have not been conducted. In this study, to reflect the spatial distribution of the farms, probability
sampling using Kernel density estimation was conducted to select 1:4 case-control. K-functions were
estimated to quantify the spatial clusters. With the agroecological variables including vegetation index
(NDVI), water index (NDWI) wind speed, elevation, slope, human population density, density for each
species and distance to traffic system and etc, Bayesian geostatistical model (Bayesian generalized
linear mixed model) was used to identify the risk factors and predict the spatial risk for HPAI H5N6.
492 control farms were selected using probability sampling. K-functions showed that the affected farms
were clustered from 500m to 10km and 13.3km to 13.8km. Bayesian geostatistical model showed that
water index (NDWI) were positively associated with the occurrence of HPAI [NDWI Odds ratios (OR):
1.313, Credential interval (CI): 1.006-1.723]. Moreover, layer density, broiler density, duck density
were positively associated (layer density OR: 2.004, CI: 1.649-2.476, broiler density OR: 1.287, CI:
1.075-1.603, duck density OR: 1.431, CI: 1.195-1.721) However, human population density was
negatively associated (human population density OR: 0.473, CI:0.237-0.809). The findings in this study
can help the policymaker to allocate the resources and build the risk-based surveillance systems
REFERENCES
[1] Magalhaes, R.J., et al., The applications of model-based geostatistics in helminth epidemiology and control.
Adv Parasitol, 2011. 74: p. 267-96.
[2] Liu, H., et al., Factors Associated with the Emergence of Highly Pathogenic Avian Influenza A (H5N1) Poultry
Outbreaks in China: Evidence from an Epidemiological Investigation in Ningxia, 2012. Transbound
Emerg Dis, 2017. 64(3): p. 746-753.
[3] Paireau, J., et al., Mapping influenza activity in emergency departments in France using Bayesian model-based
geostatistics. Influenza Other Respir Viruses, 2018. 12(6): p. 772-779.
2019 한국수리생물학회 24 2019.06.20(목) - 6.22(토)
병원체의 유전정보를 통한 병원체 전파의 재구성;
세계 말 인플루엔자 바이러스 전파에 Phylogeography의 활용
Kyuyoung Lee (이규영), Nicola Pusterla, Samantha M. Barnum, Beatriz Martínez-López
The Department of medicine and epidemiology, School of Veterinary medicine,
University of California, Davis. CA US
말 인플루엔자 바이러스 (Equine influenza virus, EIV)는 말에 상부호흡기질환을 일으키는 높은
전염성의 병원체이다. EIV는 1950 년대 첫 검출이후 전세계적으로 말 산업에 피해를 끼치고 있다.
EIV는 일반적으로 직접 접촉을 통해서 전파됨에도, 전세계적으로 유사한 유전형이 전파되는 것은
말의 지속적인 국가간 이동에 의한 것으로 알려져 있다. 최근 병원체의 유전정보를 바탕으로 한
진단법의 확대는 유전적 근연관성을 바탕으로 한 계통수 연구(Phylogenetic analysis)의 확대를
가져왔다. 최근의 연구는 전세계적으로 2011 년까지 분리된 EIV 의 염기서열을 이용하여 계통수
추정을 통한 유전적 근연관관계를 파악, 국가간 전파의 연관성을 추정하였다. 본 연구는 2017 년
12 월까지 전세계적으로 분리된 EIV 의 Hemagglutinin (HA) 유전자의 염기서열을 바탕으로 계통수
연구를 수행하였다. 더 나아가 바이러스의 역학정보와 계통수 정보를 더한 Bayesian
phylogeography을 이용해 EIV의 국가간 이동을 재구성하였다.
1963년부터 2017년까지 전세계에서 검출된 334 EIV의 HA gene 염기서열을 수집하였으며, Bayes
factor 로 선택된 1st & 2nd + 3rd partitioning Hasegawa-Kishino-Yano + Γ (8 categories)
phylogeny모델에 Exponential growth population with coalescent prior node + uncorrelated lognormal relaxed-
clock model 과 Asymmetrical Q-matrix ancestral state estimation 모델을 통하여 Phylogeography를 추정,
EIV의 전파를 추정하였다. [RevBayes V1.0.11]
현재까지 EIV FC1 아형은 미국내에서 주로 전파되며, 캐나다, 남아메리카, 일본, 한국 그리고
말레이지아로 국외 전파되는 것으로 추정된다. 그리고 EIV FC2 아형은 영국 및 일부
유럽국가에서 주로 순환되며, 아프리카, 서아시아, 인도 몽골 그리고 중국으로 전파된 것으로
추정된다. 해당연구는 최근까지 분리된 EIV 의 유전정보를 바탕으로 한 Phylogeography 를 통해
최근의 전파까지 역추적하는 결과를 보였다. 하지만 Non-probabilistic sampling 으로 수집 및
공유되는 EIV 유전정보로 인하여 잠재적으로 편향된 추정의 결과가 나타날 수 있다는 한계점을
가지고 있다. 이 연구의 결과는 전세계적인 EIV 예찰에 활용될 수 있으며, 이를 통해 국가간
전파의 형태에 따른 고위험 전파경로를 강화하는 검역 및 방역 정책수립에 활용될 것이다.
REFERENCES
[1] Murcia, P. R., Wood, J. L. & Holmes, E. C. Genome-scale evolution and phylodynamics of equine H3N8
influenza A virus. Journal of virology 85, 5312–5322 (2011).
[2] Pybus, O. G. & Rambaut, A. Evolutionary analysis of the dynamics of viral infectious disease. Nature Reviews
Genetics 10, 540 (2009).
[3] Höhna, S. et al. RevBayes: Bayesian phylogenetic inference using graphical models and an interactive model-
specification language. Systematic Biology 65, 726–736 (2016). Gardy, J. L. & Loman, N. J.
[4] Towards a genomics-informed, real-time, global pathogen surveillance system. Nature Reviews Genetics 19,
9 (2018).
2019 한국수리생물학회 25 2019.06.20(목) - 6.22(토)
Session A2
Transmission dynamics of Tuberculosis disease
Organizer: 김소영 (건국대학교)
Date/Time: 6월 21일(금) 09:00
Speakers:
1. Hee Jin Kim (The Korean National Tuberculosis Association)
2. Sunhwa Choi (National Cancer Center)
3. Soyoung Kim (Kunkuk University)
2019 한국수리생물학회 26 2019.06.20(목) - 6.22(토)
Basic Epidemiology of Tuberculosis needed for Mathematical
Modelling of Tuberculosis
Hee Jin Kim, M.D.
Central Training Institute, The Korean National Tuberculosis Association
The World Health Organization has established an “End TB Strategy,” which aims to reduce
the incidence of tuberculosis (TB) worldwide by less than 10/105 population by 2035. Korea
has high morbidity rate compared to the socioeconomic level. In 2018, 26,433 (51.5/105) new
TB patients were notified, which is the most serious among OECD countries. The government
has been actively coping with the establishment of mid-term national control strategies. As a
result, the average annual decline rate in new patients is 5.9% since 2011, which is significantly
higher than the global annual decline rate of 2 % in TB incidence. Recently the 2nd National
Strategic Plan for TB control 2018-2022 was announced. The goal is to reduce the TB incidence
to 40/105 by 2022 and to 10/105 by 2030. Considering the estimated incidence rate of 70/105
in 2017, it is only possible to reduce by 14% per year in order to achieve the 2030 target.
To carry out an effective TB control programs, it is necessary to estimate the current and future
burden and trend of TB. In addition, once a model is developed that can predict how much each
TB prevention and care program can reduce the burden of disease, it will be able to conduct
more efficient programs.
In order for the mathematical model to accurately reflect the real situation, it is necessary to
understand the natural history of TB as well as epidemiological data of current TB status,
attributable factors to the incidence of TB, and contribution of interventions to reduce the
incidence when implemented.
In this talk, I introduce the natural history of TB focused on infection and development of TB,
contribution of endogenous reactivation and exogenous reinfection according to age. In
addition, the current situation of TB in Korea, precautions in applying the notified data, and
major risk factors such as nutritional deficiency, smoking, diabetes, alcohol drinking is
presented. Finally I introduce the latent TB infection management program which is being
promoted as a major preventive program.
REFERENCES
[1] Global tuberculosis report 2018. Geneva: World Health Organization; 2018. License: CC BY-NC-SA 3.0 IGO.
[2] Korea Centers for Disease Control and Prevention. Annual report on the notified tuberculosis in Korea 2018.
Cheongju, Osong, 2019.
[3] Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. The 2nd National Strategic
Plan for Tuberculosis Control. News Briefing, 28 May 2019.
2019 한국수리생물학회 27 2019.06.20(목) - 6.22(토)
Mathematical Modeling of Tuberculosis in the Republic of Korea
Sunhwa Choi
Department of Cancer Control and Population Health
Graduate School of Cancer Science and Policy, National Cancer Center
In this talk, we present the mathematical models of tuberculosis (TB) currently used in the
Republic of Korea, both for understanding the basic science of the disease process and also for
practical issues such as preventing TB spread and evaluating the TB control strategies. The
mathematical models for TB dynamics have been developed in order to estimate the potential
impact of epidemic of TB infection. The incorporating of optimal control theory into the
tuberculosis model suggests policy decisions regarding TB infection control and outbreak
response plans, which determines the best possible strategy for TB care and estimates the
resources needed for the response.
REFERENCES
[1] Choi S, Jung E, Lee SM. Optimal intervention strategy for prevention tuberculosis using a smoking-
tuberculosis model. Journal of theoretical biology. 2015 Sep 7;380:256-70.
[2] Choi S, Jung E. Optimal tuberculosis prevention and control strategy from a mathematical model based on
real data. Bulletin of mathematical biology. 2014 Jul 1;76(7):1566-89.
[3] Whang S, Choi S, Jung E. A dynamic model for tuberculosis transmission and optimal treatment strategies in
South Korea. Journal of theoretical biology. 2011 Jun 21;279(1):120-31.
2019 한국수리생물학회 28 2019.06.20(목) - 6.22(토)
Mathematical Modeling of Tuberculosis transmission in the high
Tuberculosis burden countries
Soyoung Kim1, Aurelio A. de los Reyes V2 and Eunok Jung1*
1Department of Mathematics, Konkuk University 2Institute of Mathematics, University of the Philippines Diliman
Tuberculosis (TB) is one of the top 10 causes of death in the world. Millions of people are
suffering from the TB disease. However, the severity of the disease differs among countries. In
high-income countries, 10 new cases per 100,000 population were reported, while 150-400
cases in most of the 30 high TB burden countries. Recently, the 30 high TB burden countries
accounted for 87% of estimated cases worldwide. In this talk, a mathematical model of
Tuberculosis transmission is introduced. For each country, the epidemic parameters are
estimated and analyzed. According to the estimated parameters, the country-specific
intervention strategies are suggested.
REFERENCES
[1] Kim, S., Aurelio, A., & Jung, E. (2018). Mathematical model and intervention strategies for mitigating
tuberculosis in the Philippines. Journal of theoretical biology, 443, 100-112.
2019 한국수리생물학회 29 2019.06.20(목) - 6.22(토)
Session A3
Mathematical Model & Optimization
Organizer: 김상일 (부산대학교)
Date/Time: 6월 21일(금) 09:00
Speakers:
1. Young-jin Kim (Pusan National University)
2. Geunsoo Jang (Pusan National University)
3. Seungheon Yi (Pusan National University)
4. Taehyeong Kim (Pusan National University)
2019 한국수리생물학회 30 2019.06.20(목) - 6.22(토)
Optimal Constant for Generalized Diagonal Update Method
Young-jin Kim
Finance· Fishery· Manufacture Industrial Mathematics Center on Big Data,
Pusan National University,
The quadratic matrix equation AX2 +BX +C = 0 can be solved by many methods and the
sufficient condition. In particular, the diagonal update method can be used in the Bernoulli’s
method and have better results remaining monotonicity convergent. This concept can be
extended more general quadratic matrix equation. In this talk, we will suggest the optimal
constant which guarantee the monotone convergence and extent the sufficient condition to
use the diagonal update method. Moreover, we also show the sequence which defined by the
diagonal update method is closer than the sequence which defined by pure iteration method.
REFERENCES
[1] Y.-J. Kim and H.-M. Kim. Diagonal update method for a quadratic matrix equation. Appl. Math. Comput.,
283, 208-215 (2016).
[2] Z.-Z. Bai, Y.-H. Gao. Modified Bernoulli iteration methods for quadratic matrix equation. Math. Comp.
25(5):498-511, 2007.
[3] Z.-Z. Bai, X.-X. Guo, and J.-F Yin. On two iteration methods for the quadratic matrix equations. Int. J.
Numer. Anal. Model., (2):114-122, 2005.
2019 한국수리생물학회 31 2019.06.20(목) - 6.22(토)
Optimal Control Strategies for Common Squid
(Todarodes Pacificus) in South Korea
1Geunsoo Jang and 2Giphil Cho
1Department of Mathematics, Pusan National University, Busan, Republic of Korea
2Finance Fishery Manufacture Industrial Mathematics Center on Big Data
Pusan National University, Busan, Republic of Korea
As the catch of common squid(Todarodes pacificus) has been decreasing continuously in
South Korea, systematic fishing management for the catch is needed. We proposed optimal
harvest strategies using a discrete population model. Common squid consists of two main
spawning stocks: autumn and winter. We represented seasonal movements of two populations
for four cohort using transition matrices. Fishing efforts in three cohorts is used as a harvest
control to maximize the profit of fishing. The Pontryagin’s maximum principle is used to solve
the optimal control problem. Simulation results show the difference of the harvest strategies of
three cohorts and maximum sustainable yield the harvest strategies for the common squid.
REFERENCES
[1] Song, H., Fluctuations of Common Squid Todarodes pacificus Catches in the Northwestern Pacific under
Changing Climate and Habitat Temperature. Korean Journal of Fisheries and Aquatic Sciences, 51(3), 338-343
(2018).
[2] Dine, W., Lenhart, S., and Behncke, H., Discrete time optimal harvesting of fish populations with age structure.
Letters in Biomathematics, 1(2), 193-207 (2014).
2019 한국수리생물학회 32 2019.06.20(목) - 6.22(토)
An optimal route recommendation system for ships
based on A* search algorithm
Taehyeong Kim and Seungheon Yi
Department of Mathematics, Pusan National University, Busan, Republic of Korea
In this study, an optimal route recommendation algorithm for ships has been developed
with the starting and ending information of time and locations. The algorithm calculates
optimal route considering various data such as marine climate and weather forecast from
Copernicus and ECMWF. We employ weighted A* search algorithm for those data we
obtained. Our numerical results are compared with the actual route of a ship.
REFERENCES
[1] Dongjun Kim, Hyeonju Seol and Junju Kim, A Study on Ship Path Planning Algorithm based on Real-time
Ocean Environment, Journal of the KIMST, 19, 252-260 (2016)
[2] Jinmo Park, and Nakwan Kim, Two-Phase Approach to Optimal Weather Routing Using Real-Time Adaptive
A* Algorithm and Geometric Programming, Journal of Ocean Engineering and Technology, 29(3), 263-269
(2015)
2019 한국수리생물학회 33 2019.06.20(목) - 6.22(토)
Session B1
Cancer and cellular mechanism
Organizer: 김양진 (건국대학교)
Date/Time: 6월 21일(금) 13:50
Speakers:
1. Yangjin Kim (Konkuk University)
2. Honda Naoki (Kyoto University, Japan)
3. Kyung-Hee Chun (Yonsei University)
4. Hyeongi Kim (Korea Institute of Radiological & Medical Sciences)
5. Aurelio A. de los Reyes V (Konkuk University)
2019 한국수리생물학회 34 2019.06.20(목) - 6.22(토)
Overview: Recent advances in tumor growth modeling
Yangjin Kim
Department of Mathematics, Konkuk University, Republic of Korea
Tumor microenvironment (TME) plays an important role in regulation of tumor growth and
cancer cell invasion. For example, many microenvironmental factors such as extracllular matrix,
microglia and astrocytes can either block or enhance this critical infiltration step in brain. We will
discuss recent advances in tumor growth modeling. Various mathematical models can be used
in order to address the complex regulation of intracellular, intercellular, and macroscale
dynamics of tumor growth. Some examples of these models will be given. We discuss how to
integrate these factors in the context of tumor modeling.
REFERENCES
[1] Yangjin Kim, Ji Young Yoo,…,Balveen Kaur and Avner Friedman, “Complex role of NK cells in regulation
of oncolytic .., PNAS, 115 (19) 4927-4932, 2018.
[2] Yoo J, et al., Bortezomib-induced unfolded protein response..,Clin Cancer Res , Vol. 20(14), 3787-3798, 2014.
[3] Yangjin Kim, ..Sean Lawler, and Mark Chaplain, Role of extracellular matrix and microenvironment.., PLoS
One, 13(10):e0204865, 2018.
[4] Barker et al, Nature Rev Cancer, 15(7), 409-25, 2015.
[5] Yangjin Kim, …, Hans G. Othmer, “Synergistic effects of bortezomib-OV therapy and anti-
invasivestrategies.., Cancers, 11(2), 215, 2019.
[6] Yangjin Kim, …, Sean Lawler, Role of tumor-associated neutrophils in regulation of tumor growth i
n lung cancer…, PLoS One, 14(1): e0211041, 2019.
[7] Eunok Jung, Aurelio A. de los Reyes, .., Yangjin Kim, Strategies.., PLoS One, 14(4): e0215547, Apr
23, 2019
2019 한국수리생물학회 35 2019.06.20(목) - 6.22(토)
System identification on
mechano-chemical epithelial sheet dynamics
Honda Naoki
Graduate School of Biostudies, Kyoto University, Japan
Collective migration of epithelial cells is a fundamental process of multi-cellular organisms.
Our recent study using live imaging with FRET-based biosensor discovered that cell migration
within an epithelial sheet is oriented by traveling waves of ERK activation [1]. However, how
the cells make a decision on migration direction by integrating mechano-chemical signals has
remained still elusive. Here, we performed system identification approach to extract a hidden
control role in the epithelial sheet dynamics in a data-driven manner. We first mathematically
formulated ERK-regulated intercellular mechanical interaction as a continuum mechanics
model. In this continuum model, migration velocity change is determined by several mechano-
chemical signals: cellular density, ERK activity, velocity field and their temporal and/or spatial
derivatives. We thus quantified the migration velocity and the mechano-chemical signals of all
cells by using cell tracking and image processing on time-lapse images. We analyzed their time-
series data with help of machine learning and then obtained the data-driven model, which
describes how the cells intracellularly process these mechano-chemical signals. We also
confirmed that this model has an ability to forecast cell migration, hence showing validity of
the model. Therefore, our data-driven system identification approach would be greatly
powerful to understand the mechano-chemical epithelial sheet dynamics.
REFERENCES
[1] Aoki K, Kondo Y, Naoki H, Hiratsuka T, Itoh RE and Matsuda M: Dev Cell 43, 305–317 (2017)
2019 한국수리생물학회 36 2019.06.20(목) - 6.22(토)
The role of Notch signaling in tumor microenvironment
Kyung-Hee Chun
Department of Biochemistry and Molecular Biology, Yonsei University College of Medicine
The Notch signaling pathway is evolutionarily conserved and there are four Notch receptors
(Notch1 to Notch4) and five DSL ligands (Jagged1, Jagged2, Delta-like1 (Dll1), Dll3, and
Dll4). As the DSL ligands are transmembrane proteins, Notch signaling is initiated by the
interaction of DSL ligands and Notch receptors. Their interaction leads to a proteolytic
cleavage of the Notch protein. The cleavage releases the Notch intracellular domain (NICD),
which translocates to the nucleus. Within the nucleus, NICD forms a complex with the DNA
binding protein RBPjk and a member of the Mastermind-like (MAML) family transcriptional
coactivators. This complex of proteins then activates the transcription of Notch target genes,
including members of Hes and Hey family, cyclinD1 and Slug. It is widely recognized that
increased Notch signaling is one of the main drivers of cellular malignancies in cancer. The
elevated expression of Notch signaling pathway components has been reported, including
Jagged1-2, Dll1, Dll3, and Dll4, Notch receptors, and Hes and Hey target genes in several
cancer types. Moreover, Notch pathway activation is commonly seen in response to targeted
therapies. Therefore, combining current treatment options with a blockade of Notch signaling
might be a feasible approach to consider. In this study, we focused on the role of notch signaling
in the tumor microenvironment. Especially, we would like to introduce Hes1, a notch target
gene as a transcriptional factor to regulate tumor cells and tumor associated macrophages.
Taken together, we suggest that Hes1 is an important target in tumor microenvironment and
further studies for clinical trials.
2019 한국수리생물학회 37 2019.06.20(목) - 6.22(토)
Derivation of mathematical modeling for the diffusion and
penetration of monoclonal antibody delivery into tumor
Hyeongi Kim1, Yangjin Kim2, and Jin Su Kim1
1) Korea Institute of Radiological & Medical Sciences, Seoul 01812, KOREA
2) Konkuk University, Seoul 05030, KOREA
Corresponding Author: Jin Su Kim, [email protected]
Although radioimmuno therapy (RIT) was effective for cancer treatment, RIT have a limited
performance in solid tumor due to highly distributed extra-cellular matrix (ECM) inside solid
tumor tissue [1,2]. In our previous study, we developed the combination RIT approaches to
enhance the penetration of monocolonal antibody (mAb). In this study, we developed the
mathematical modeling for describing the diffusion and penetration of mAb into tumor.
Reaction-diffusion partial differential equations (PDE) was developed for describing the
dependency of cancer cell, ECM density, diffusion and penetration of mAb and oncolytic virus.
Initial condition for solving the PDE was derived using our experimental result of same design.
Diffusion coefficient and reaction parameter for mAb and oncolytic virus was modelled for
simulating actual behavior of mAb and oncolytic virus. Various condition of ECM density
(10%-90%), ECM structure, and vessel density were modelled which was derived actual the
result of MT staining or distribution of collagen type I and the distribution of active vessel.
Our developed mathematical modeling was validated with experimental result due to well
defined based initial condition which was derived from actual experimental result. Diffusion
and penetration of mAb and oncolytic virus were well described for extravasation of mAb from
tumor vessel and tumor surface. All ECM structure was degraded regardless of ECM structure
at 50 hr after spreading of oncolytic virus. Therefore 2.3 times greater amount of mAb was
accumulated in whole tumor tissue at 50 hr after spreading of oncolytic virus and diffusion of
mAb compared to only mAb injection group. The pattern of degradation of ECM structure and
accumulation of mAb were well matched with our experimental results. Our newly developed
mathematical model could describe the diffusion of mAb in the region of tumor vessel and
tumor surface. We could derive the optimal dose and dose scheduling of mAb for RIT based
on our developed mathematical modeling.
2019 한국수리생물학회 38 2019.06.20(목) - 6.22(토)
In this works, we developed new theoretical mathematical model approach. Strikingly, in
the current model, can be useful to describe detailed mechanical effects such as mAb and virus
penetration of a tumor. And the model predicts mAb therapy effects with Oncolytic virus,
depending on ECM density and structure. Moreover, predicts the optimal mAb therapy with
oncolytic virus depending on tumor microenvironments.
The mathematical modeling of mAb/Ad3-RLX
Figure 1. The schematic of combination immuno therapy strategies and equation.
Figure 2. The effect of degradation of extracellular matrix after combination immuno therapy
strategies
REFERENCES
[1] Kim J.S., “Combination Radioimmunotherapy Approaches and Quantification of Immuno-PET” Nucl Med
Mol Imaging, Vol. 50, 2016, pp. 104-111.
[2] Zaheer Z, Kim H, Lee Y-J, Lim S.M., and Kim J.S., “Radioimmunotherapy and its strategies for solid tumor”,
submitted
2019 한국수리생물학회 39 2019.06.20(목) - 6.22(토)
Control Strategies for Glioblastoma Therapy
Aurelio A. de los Reyes V, Eunok Jung and Yangjin Kim
Department of Mathematics, Konkuk University
Glioblastoma multiforme is the most lethal form of brain cancer. Even with the current
standard of care, glioblastoma treatment remains a laborious challenge. The mean survival time
is about a year after diagnosis. In this talk, we present a model of intracellular signaling
pathway in glioblastoma. It consists of the miR-451–AMPK–mTOR core control linked to the
cell cycle dynamics. The model captures the dichotomy of rapid proliferation and aggressive
invasion in glioma cells. Optimal control theory is utilized to regulate the switching behavior
of the cells between growth and migration to neighboring tissues. The up-stream signaling
pathway is regulated via glucose infusion enhancing miR-451 activities. The down-stream
pathway to the cell cycle is controlled via drug infusion upregulating mTOR. The goal of the
optimal control problem is to restrain cell growth and reduce cell invasion to the surrounding
tissue. Concomitant and alternating glucose and drug infusion schemes are investigated under
various circumstances to explore anti-invasion therapeutic strategies with minimal cost.
REFERENCES
[1] E. Jung, A.A. de los Reyes V, K.J.A. Pumares and Y. Kim, Strategies in regulating glioblastoma signaling
pathways and anti-invasion therapy, PloS ONE, 14(4), e0215547 (2019)
[2] Y. Kim, H. Kang, G. Powathil, H. Kim, et al., Role of extracellular matrix and microenvironment in regulation
of tumor growth and LAR-mediated invasion in glioma, PloS ONE, 13(10), e0204865 (2018)
[3] A.A. de los Reyes V, Y. Kim and E. Jung, Optimal control strategies of eradicating invisible glioma cells after
conventional surgery, Journal of Royal Society Interface, 12, 20141392 (2015)
2019 한국수리생물학회 40 2019.06.20(목) - 6.22(토)
Session B2
A practical approach to retrieval and
analysis of biomedical data
Organizer: 박용근 (가톨릭관동대학교)
Date/Time: 6월 21일(금) 13:50
Speakers:
1. Yongkeun Park (Catholic Kwangdong University)
2. Min Geun Park (Catholic Kwangdong University)
3. Dukyong Yoon (Ajou University)
4. Bumhee Park (Ajou Uinversity)
2019 한국수리생물학회 41 2019.06.20(목) - 6.22(토)
MicroRNAs associated with vascular invasion in hepatocellular
carcinoma and their prognostic significance: an analysis using
publicly available genomic databases
Yongkeun Park
Catholic Kwandong University College of Medicine
Department of Surgery, CKU International St. Mary’s Hospital
Hepatocellular carcinoma (HCC) has received increasing attention because of its frequent
diagnosis worldwide with a dismal prognosis [1]. A significant contributor to poor outcomes is
the tendency of HCC toward vascular invasion (VI) which reflects the tumor’s aggressiveness
[2,3]. Therefore, altered or disrupted regulatory mechanisms contributing to VI in tumor cells
a barrier to overcoming this cancer and so are candidate targets for a new therapeutic trial.
Recently, critical roles of small ncRNAs including microRNAs (miRNAs, miRs) and piwi-
interacting RNAs (piRNAs) in a variety of human diseases, particularly cancers, have been
well elucidated [4,5]. These RNAs have been shown to play an important role in tumorigenesis
and/or tumor progression. Some of these RNAs can regulate epithelial–mesenchymal transition
(EMT) directly or indirectly. Thus, they are involved in tumor invasion or metastasis [6]. But,
few studies have investigated the relationship between gross VI and aberrant expression of
microribonucleic acids (miRNAs and miRs). Thus, the objective of this study was to identify
miRNAs selectively expressed in HCC with gross VI and investigate their prognostic
significance. Eligible two datasets (accession number: GSE20594 and GSE67140) were
collected from the National Center for Biotechnology Information’s (NCBI) Gene Expression
Omnibus (GEO) database to compare miRNAs expression between HCC with and without
gross VI. Differentially expressed miRNAs were externally validated using expression data
from The Cancer Genome Atlas (TCGA) database. Prognostic significance and predicted
functions of selected miRNAs for HCC were also investigated. Thirty-five miRNAs were
differentially expressed between HCC with and without gross VI in both datasets. Among them,
2019 한국수리생물학회 42 2019.06.20(목) - 6.22(토)
four miRNAs were validated using TCGA database. miR-582 was upregulated to a greater
extent while miR-99a, miR-100, and miR-148a were downregulated to a greater extent in
patients with HCC and gross VI than in those with HCC but no VI. Receiver operating
characteristic (ROC) curve analysis showed discriminatory power of these miRNAs in
predicting gross VI. Multivariate survival analysis revealed that types of surgery, advanced
tumor node metastasis (TNM) stage, and miR-100 underexpression were independently
associated with tumor recurrence. It also revealed that types of surgery, advanced TNM stage,
miR-100 underexpression, and miR-582 overexpression were independent risk factors for
overall survival (OS) after hepatic resection for HCC. A text mining analysis revealed that these
miRNAs were linked to multifaceted hallmarks of cancer, including “invasion and metastasis.”
This study showed that miR-100-5p was underexpressed while miR582-3p was overexpressed
to a great extent in HCC tissues with gross VI than that in HCC tissues without gross VI. In
addition, their aberrant expressions were significantly associated with poor survival of patients
after hepatic resection for HCC.
REFERENCES
[1] Torre LA, et al. Global cancer statistics, 2012. CA: a cancer journal for clinicians. 65, 87-108 (2015)
[2] Zhang G, et al. Validation of the American Joint Committee on Cancer eighth edition staging system in patients
undergoing hepatectomy for hepatocellular carcinoma: a US population-based study. J Surg Res. 222, 55-68
(2017).
[3] Park YK, et al.. Prognostic significance of microvascular invasion in tumor stage for hepatocellular carcinoma.
World J Surg Oncol. 15,225 (2017)
[4] Esteller M. Non-coding RNAs in human disease. Nature reviews Genetics. 12,861-874 (2011)
[5] Liu Y. MicroRNAs and PIWI-interacting RNAs in oncology. Oncol Lett. 12,2289-2292 (2016)
[6] Li PF, et al. Non-coding RNAs and gastric cancer. World J Gastroenterol. 20,5411-5419 (2014).
2019 한국수리생물학회 43 2019.06.20(목) - 6.22(토)
Prediction of disease-free survival via gene - DNA methylation signature
model and machine learning model in stage I-II colorectal cancer patient
Min Geun Park
Department of Surgery, CatholicKwandong University, International St. Mary’s Hospital
Background: Since patients with high risk factors should receive chemotherapy in early colorectal
cancer, it is worthwhile to investigate the prognostic genetics, which can play a role as a high risk factor,
in early colorectal cancer.
Purpose: My objective is to develop a three-gene and DNA methylation signature model and machine
learning model for predicting disease-free survival of stage I-II colorectal cancer.
Method: mRNA and DNA methylation data sets of colorectal cancer patients from The Cancer Genome
Atlas (TCGA) were obtained. I found inverse correlation coefficient genes between mRNA expression
and DNA methylation (Pearson’s correlation coefficient < -0.4). Then, differentially expressed genes
(DEGs, FDR <0.05 with Wilcoxon rank-sum test) and differentially methylated DNAs (DMDs, β-value
difference ≥ 0.05 & M-value difference ≥ 0.5 & FDR < 0.05 with Wilcoxon rank-sum test) were
identified between recurrence group and others. Machine learning modeling and gene-DNA
methylation signature modeling were performed using genes (FABP2, SGEF, SHISA9) commonly
identified in the DEGs and the DMDs lists. Gene-DNA methylation signature model was as follows:
Prognostic risk score = ∑Cox coefficients for mRNA expression of genei × expression value of genei +
∑Cox coefficients for DNA methylation of genei × methylation β-value of genei
A risk score was calculated as the summation of weighted expression levels and methylation level with
coefficients by Cox analysis. Patients were divided into high-risk and low-risk groups using the 50th
percentile cut-off of the prognostic risk score of the three-gene and DNA methylation signature. The
prognostic risk scores and the cut-off score derived from the training cohort(n=61) were not re-
estimated and then applied to the 2 testing cohorts (n=59 & 57). The machine learning model algorithms
was logistic regression with Tensorflow. The training cohort and 2 testing cohorts were used in analysis
of machine learning model.
Results: In gene-DNA methylation signature model, risk scores were statistically significant in
multivariate Cox analysis (Training cohort: HR 10.45 p-value 0.0262, Testing cohort1: HR 5.308 p-
value 0.0352, Testing cohort2: HR 5.692 p-value 0.0396). In machine learning model, accuracy of
predicting recurrence in training cohort, testing cohort1 and testing cohort2 were 83.60%, 83.05% and
85.96%.
Conclusion: The gene-DNA methylation signature model and the machine learning model can be used
to predict the disease-free survival among patients with stage I-II colorectal cancer.
2019 한국수리생물학회 44 2019.06.20(목) - 6.22(토)
Development of artificial intelligence models for early warning
system in intensive care unit
Dukyong Yoon
Department of biomedical informatics, Ajou University School of Medicine, Suwon, Korea
Recent artificial intelligence (AI) technology which outperforms in diverse area is being expected to
be successfully implemented in medical field in near future. Many studies have shown that the accuracy
of artificial intelligence is better than physicians in not only diagnosis but also treatment.(1,2) However,
it is fact that there is big discrepancy between current AI technology and the expectation or imagination
of physicians working in real practice. To reduce confusion in process of applying new technology, we
need to have understanding on that.
AI is broad terminology which covers all computational agent which mimics human’s cognitive
function. Machine learning is subordinate concept of AI, which refers the process of finding certain
patterns from given data. Machine learning can be categorized into three categories as unsupervised,
supervised, and reinforcement learning. Unsupervised learning can be used for abstracting complex
high-level concept of raw medical data. For development of diagnosis model, supervised learning has
been usually used. In clinical practice, making treatment policy is also important, in this case
reinforcement learning would be useful. The process for apply AI in medicine has following steps: data
acquisition, data preprocessing & abstracting, and developing models for prediction or making policy.
To development of advanced AI models in critical care area, Ajou University Medical Center
(AUMC) have tried to construct infrastructure for automatically collecting diverse valuable data which
were usually observed in intensive care units or operating rooms and useful to determine patients’ status
but not have been usually collected in most other hospitals; bio-signals (electrocardiogram, arterial
blood pressure, and etc.), parameters of mechanical ventilators, pupilometer, or cerebral oximetry. With
these data, AUMC have developed or will develop AI models which is able to help clinicians working
in critical care area (for example, predicting sepsis, arrest, or failure of ventilator weaning).
In not-so-distance future, AI will be able to collect data, conduct diagnosis, and provide treatment
plan more efficiently, properly, and effectively than human. We need to find the way to co-work with
AI models with the view of promoting health quality of the patients.
REFERENCES
[1] Komorowski M, Celi LA, Badawi O, Gordon AC, Faisal AA. The Artificial Intelligence Clinician learns
optimal treatment strategies for sepsis in intensive care. Nat Med. 2018;24(11):1716-1720.
[2] Ting DSW, Cheung CY, Lim G, et al. Development and Validation of a Deep Learning System for Diabetic
Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.
JAMA. 2017;318(22):2211-2223.
2019 한국수리생물학회 45 2019.06.20(목) - 6.22(토)
Complex Brain Network Analysis: An Introduction
Bumhee Park1,2
1Department of Biomedical Informatics, Ajou University School of Medicine
2Office of Biostatistics, Ajou Research Institute for Innovative Medicine, Ajou Unversity Medical
Center
The human brain can be understood as a complex system or network, where brain functions
emerge from the interaction between neurons at multiple levels. Connectomics is a research
field that seeks to collect and analyze such information about neural interaction, which has
greatly advanced our understanding of the brain. This talk will introduce how the brain network
can be constructed using diverse neuroimaging techniques and characterized using various
methodological approaches for investigating brain functions.
Keywords: connectivity, connectome, neuroimaging, graph theory
2019 한국수리생물학회 46 2019.06.20(목) - 6.22(토)
Session B3
신약개발 모델링
Organizer: 윤강준 (국가수리과학연구소)
Date/Time: 6월 21일(금) 13:50
Speakers:
1. 김병천 (국가수리과학연구소)
2. Yong Sul Won (국가수리과학연구소)
3. Gangjoon Yoon (국가수리과학연구소)
2019 한국수리생물학회 47 2019.06.20(목) - 6.22(토)
Prediction of Kinase-Inhibitor Activity
김병천
수학원리응용센터, 국가수리과학연구소
신약개발 초기단계에서 수행하는 HTS(High-Throughput Screening)에 대해
알아보고, Deep Learning을 사용한 QSAR(Quantitative Structure-Activity
Relationship)기반 Virtual Screening Model을 살펴본다. Kaggle Merck Molecular Activity
Challenge에서 우승한 Multi-task Neural Network[1]에 Morgan fingerprint를 적용한
사례와 화합물을 표현하는 SMILES code와 Kinase를 표현하는 protein sequence를
사용한 DeepDTA[2]의 사례를 소개한다.
REFERENCES
[1] George E. Dahl and Navdeep Jaitly, Multi-task Neural Networks for QSAR Predictions, arXiv:1406.1231v1
[stat.ML] (2014)
[2] Hakime Öztürk, Arzucan Özgür and Elif Ozkirimli, DeepDTA: deep drug–target binding affinity prediction,
Bioinformatics, 34, i821–i829 (2018)
2019 한국수리생물학회 48 2019.06.20(목) - 6.22(토)
Global very weak solution for a nonlinear population model with
spatial heterogeneity
Yong Sul Won
Center for Applications of Mathematical Principles
National Institute for Mathematical Sciences
In this talk, we present the global well-posedness results of a degenerate nonlinear parabolic
equation. The equation exhibits dispersions of ecological species whose motility is determined
by the environmental conditions, particularly the availability of nourishments to biological
species. Such ideas have already been reflected in the ecological modelling and is now known
as Starvation Driven Diffusions (SDD) [1]. However, in exchanges for realistic modelling,
some constraints of the SDD model may become singular, when population density becomes
zero. To avoid such irregular situations, we employ a regularisation scheme and the
corresponding notion of a very weak solution. Then the solutions need not stay strictly positive,
and thus, our analysis can incorporate some important ecological phenomena such as the
extinction of species. Furthermore, the above very weak solution may recover classical solution
provided sufficient regularity conditions. This project forms a part of the PhD research [2] and
writing is in progress for submission.
REFERENCES
[1] E. Cho and Y. J. Kim, Starvation driven diffusion as a survival strategy of biological organisms, Bulletin of
Mathematical Biology, 75, 845-870 (2013)
[2] Y. S. Won, Analysis of linear and nonlinear dissipative systems, PhD Thesis, Imperial College London (2018)
2019 한국수리생물학회 49 2019.06.20(목) - 6.22(토)
Monolithic Image Decomposition:
Structure-Texture Extraction Method
Gangjoon Yoon
수학원리응용센터, 국가수리과학연구소
Image decomposition is one of the essential image processing techniques in computer vision
and computational photography because it can be applied to various areas, such as image
smoothing, detail enhancement, image abstraction, and high-dynamic-range compression.
The main goal of image decomposition is to successfully separate structure from a given image
by preserving structure components like edges and removing fine-scale details without prior
information.
In this talk, we propose an effective image decomposition technique [1], which is called a
monolithic image decomposition, that considers both local and global features using RGB color
channels simultaneously by exploiting low-rank approximation and total variation-based
minimization while previous approaches use either local or global features, and perform the
image decomposition process channel by channel and combine the decomposition result of
each channel. Using monolithic parameter update, we successfully separate the texture and
structure from a given image while preventing artifacts such as staircase effects instead of
traditional staggered methods.
The experiment results prove the effectiveness of our approach in image decomposition.
We also show the usefulness of our approach by presenting successful applications in structure-
texture-noise decomposition, detail enhancement and image abstraction.
REFERENCES
[1] J. Song, G. Yoon and S. Yoon, Monolithic Image Decomposition, Neurocomputing, 2019, accepted.
2019 한국수리생물학회 50 2019.06.20(목) - 6.22(토)
Session C1
Mathematics and Statistics on the spread of
infectious disease
Organizer: 손우식 (국가수리과학연구소)
Date/Time: 6월 21일(금) 15:40
Speakers:
1. 심은하 (숭실대학교)
2. 이종걸 (국가수리과학연구소)
3. 김선월 (국립중앙의료원)
4. 손우식 (국가수리과학연구소)
2019 한국수리생물학회 51 2019.06.20(목) - 6.22(토)
Interplay of mathematical epidemiology and economic
considerations
Eunha Shim*, Smith KJ, France G, Nowalk MP, Raviotta JM, DePasse J, Wateska A,
and Zimmerman RK.
*Department of Mathematics, Soongsil University
With mathematical modeling of infectious diseases and the evolution of pathogens, we can
provide insights into predicting health policy effectiveness and best practices. Health policies
must be developed to maximize the benefit to the public and to balance health, social, and
economic considerations. For instance, in light of recent influenza vaccine efficacy data in U.S.
and relatively low dengue vaccine efficacy data in Latin America, we used a mathematical
model to evaluate epidemiological and economic impact of both vaccination programs in
international settings. For such a practical application, mathematical models with economic
considerations including game theory application often involves molecular, individual,
population, and national scales, and they are developed from evolutionary perspectives.
REFERENCES
[1] Shim E, Smith KJ, Patricia Nowalk M, Raviotta JM, Brown ST, DePasse JV, and Zimmerman RK, Impact of
seasonal influenza vaccination in the presence of vaccine interference, Vaccine, 36(6):853-858 (2018)
[2] Shim E. Optimal dengue vaccination strategies of seropositive individuals, Mathematical Biosciences and
Engineering, 16(3):1171-1189 (2019)
[3] Shim E, Chapman GB, Townsend JP, Galvani AP, The influence of altruism on influenza vaccination decisions,
Journal of the Royal Society Interface, 9(74): 2234-2243 (2012)
2019 한국수리생물학회 52 2019.06.20(목) - 6.22(토)
Spatial heterogeneity and control measures during avian
influenza epidemic 2016-2017 in Korea
Jonggul Lee, Youngsuk Ko, and Eunok Jung
Division of Medical Mathematics, National Institute for Mathematical Sciences
During the winter of 2016-2017, an epidemic of highly pathogenic avian influenza (HPAI)
led to high mortality in poultry and put a serious burden on the poultry industry of the Republic
of Korea. Effective control measures considering spatial heterogeneity to mitigate the HPAI
epidemic is still a challenging issue. Here we develop a spatial-temporal compartmental model
that incorporates the culling rate as a function of the reported farms and farm density in each
town. The epidemiological and geographical data of two species, chickens and ducks, from the
farms in the sixteen towns in Eumseong-gun and Jincheon-gun are used to find the best-fitted
parameters of the metapopulation model. The best culling radius to maximize the final size of
the susceptible farms and minimize the total number of culled farms is calculated from the
model. The local reproductive number using the next generation method is calculated as an
indicator of virus transmission in a given area. Simulation results indicate that this parameter
is strongly influenced not only by epidemiological factors such as transmissibility and/or
susceptibility of poultry species but also by geographical and demographical factors such as
the distribution of poultry farms (or density) and connectivity (or distance) between farms.
Based on this result, we suggest the best culling radius with respect to the local reproductive
number in a targeted area.
REFERENCES
[1] H. Gulbudak and M. Martcheva, Forward hysteresis and backward bifurcation caused by culling in an avian
influenza model, Math. Biosci., vol. 246, no. 1, pp. 202–212, 2013.
2019 한국수리생물학회 53 2019.06.20(목) - 6.22(토)
응급실 기반 감염병 자료 자동수집 및
분석시스템 구축 전략연구
김선월
국립중앙의료원
본 연구는 응급실 기반 감염병 조기 감시 및 대응체계 구축을 위해 국가응급진료정보망(NEDIS)
자료를 이용하여 타당성을 검토하고, 타 자료원과의 감염병 발생현황을 비교 분석하였다. 감염병
발생 위험경보를 위해서는 시간적 분석 모형과 시공간적 분석방법을 이용하여 적합한 모형을 선
정하기 위한 실험결과를 제시하였다. 또한 SNS 자료를 이용한 증후군 감시의 타당성 검토를 위하
여 대중의 관심도나 최근 유행을 고려하여 질환을 선정하고, SNS 탐색량과 NEDIS 자료와의 비교
분석을 수행하였다. 마지막으로 연구결과를 토대로 응급실 기반 자동수집을 위한 모니터링 시스
템 구축 현황을 소개한다.
2019 한국수리생물학회 54 2019.06.20(목) - 6.22(토)
The characteristics of regional and age-group-specific spread of
influenza in Korea
Woo-Sik Son
National Institute for Mathematical Sciences
For mitigation strategies of an influenza outbreak, it can be helpful to understand the
characteristics of regional and age-group-specific spread. Such as, in which region and in which
age-group does an influenza outbreak begin first? Then, how does it spread by region and age-
group? In Korea, however, there has been no official statistic related to it. In this study, we
extract the time series of influenza incidence from National Health Insurance Service claims
database, which consists of all medical and prescription drug-claim records for almost all
Korean population. The extracted time series contains the number of influenza patients by
region (250 city-county-district) and age-group (0~4, 5~19, 20~64, 65+) with in a week from
2009 to 2016. Then, we show that the metropolitan area and 0~4, 5~19 age-groups are faster
than other regions and age-groups for both the start and peak of an influenza outbreak. These
results would be helpful to design a surveillance system for timely early warning of an
influenza outbreak.
2019 한국수리생물학회 55 2019.06.20(목) - 6.22(토)
Session C2
Research on mathematical modeling of human body
Organizer: 이완호 (국가수리과학연구소)
Date/Time: 6월 21일(금) 15:40
Speakers:
1. Wanho Lee (National Institute for Mathematical Sciences)
2. Sookkyung Lim (University of Cincinnati)
3. Tae-Rin Lee (Seoul National University)
4. Seunggyu Lee (National Institute for Mathematical Sciences)
2019 한국수리생물학회 56 2019.06.20(목) - 6.22(토)
Prediction of Cardiac Function using Patient's Blood Pressure
Data
Wanho Lee1, Jin-Ho Choi2, and Eunok Jung3
1) Division of Medical Mathematics, National Institute for Mathematical Sciences,
Daejeon 34047, KOREA
2) Department of Internal Medicine, Department of Emergency Medicine, Samsung Medical Center,
Seoul 06351, KOREA
3) Department of Mathematics, Konkuk University, Seoul 05029 KOREA
In this talk, the study of prediction of cardiac function by using the blood pressure data of
patient as a constraint of mathematical model is presented. We use a lumped model consisting
of six compartments: left ventricle, right ventricle, systemic artery, systemic vein, pulmonary
artery, and pulmonary vein. Six compartments are treated as compliant chambers and they are
connected by resistance vessels, so it makes one loop. We estimated the pumping function of
heart from the blood pressure data using the least-square fitting. We compared the cardiac
functions, such as SV (stroke volume) and EF (ejection fraction) of left ventricle, between
simulation results and observed data.
2019 한국수리생물학회 57 2019.06.20(목) - 6.22(토)
Bacterial swimmers propelled by helical flagella
Sookkyung Lim
Department of Mathematical Sciences, University of Cincinnati
Swimming bacteria with helical flagella are self-propelled micro-swimmers in nature, and
the swimming strategies of such bacteria vary depending on the number and the position of
flagella on the cell body. In this talk, we will introduce two microorganisms, multi-flagellated E.
coli and single-flagellated Vibrio A. The Kirchhoff rod theory is used to model the elastic
helical flagellum and the penalty method is employed to describe the dynamics of the rigid cell
body. The hydrodynamic interaction between the fluid and the cell is represented by the
regularized Stokes formulation. The focus of the talk will be on how bacteria reorient
swimming direction
2019 한국수리생물학회 58 2019.06.20(목) - 6.22(토)
Predicting the Hemodynamics at the Microvascular-Network
Level with Experimental Validation
Tae-Rin Lee* and Minsin Kim
Advanced Institute of Convergence Technology, Seoul National University
Blood flow in the microvasculature is complex and heterogeneous. In the reason, it is
challenging to develop a representative model for predicting cellular transport at the
microvascular-network level. Here, we suggest a computational method in predicting the
hemodynamics. The microvascular geomtery is mathematically constructed by controlling
vessel diameters, angles and asymmetric parameters. The blood flow model in the generated
microvessls is governed by in vivo viscosity law, Poiseuille flow model and hematocrit
redistribution by plasma skimming.1) The computational model is compared with several
experimental results.2) In addition, the capability of current method is fully discussed.
REFERENCES
[1] T.-R. Lee, J.-A. Hong, S. S. Yoo and D. W. Kim, A Computational Modeling of Blood Flow in Asymmetrically
Bifurcating Microvessels and its Experimental Validation, International Jounal for Numerical Methods in
Biomedical Engineering, 34(6) (2018)
[2] J. Yang, S. S. Yoo and T.-R. Lee, Effect of Fractional Blood Flow on Plasma Skimming in the Microvasculature,
Physical Review E, 95(4-1) (2017)
2019 한국수리생물학회 59 2019.06.20(목) - 6.22(토)
Hypothesis on fingerprint pattern formation
using mathematical modelling
Seunggyu Lee1 and Young Ho Lee2
1. National Institute for Mathematical Sciences
2. Chungnam National University College of Medicine
We can find complex patterns at fingertipes of most of primates including human being, which
is called fingerprint. Since the patterns are not identical even between enzygotic twins, it has
been applied to distinguish each individuals. However, there is still no established theory about
pattern formation. In this work, we propose a mathematical model for fingerprint formation
related with distribution of sweat gland duct on curved manifold.
REFERENCES
[1] M. Kucken and A. Newell, Fingerprint formation, Journal of Theoretical Biology, 235, 71-83 (2005).
[2] S. Sick, S. Reinker, J. Timmer and T. Schlake, WNT and DKK determine hair follicle spacing through a
reaction-diffusion mechanism, Science, 314, 1447-1450 (2006)
2019 한국수리생물학회 60 2019.06.20(목) - 6.22(토)
Session C3
Mathematical modeling of biological systems and
its applications
Organizer: 윤민 (부경대학교)
Date/Time: 6월 21일(금) 15:40
Speakers:
1. Kwangsu Kim (Kyushu University)
2. Malik Muhammad Ibrahim (Pusan National University)
3. Sungchan Kim (Pusan National University)
4. Jae Hun Jung (Pusan National University)
2019 한국수리생물학회 61 2019.06.20(목) - 6.22(토)
Modeling of cell to cell infection in a growing plaque to quantify
role of amino acid mutations in GP of filovirus
Kwangsu Kim1, Tatsunari Kondoh2, Ayato Takada2 and Shingo Iwami1
1. Department of Biology, Faculty of Sciences, Kyushu University
2. Research Center for Zoonosis Control, Hokkaido University
Interaction between the filovirus (Ebola and Marburg viruses) glycoprotein (GP) and the
Niemann-Pick C1(NPC1) receptor is essential to mediate membrane fusion during the virus
entry. Some amino acid mutations in 2 loop regions of NPC1 reduced the binding to GP.
However, little is known about which amino acid mutation most effectively reduced the binding
to GP and how affect of amino acid mutation to GP. This quantitative analysis is difficult to
derive an accurate numerical value only by the existing experimental method. Toward solving
these problem, we not only conducted experiment but also developed a mathematical model to
identify a role of acid mutations in GPs of Ebola and Marburg viruses. We also have developed
a mathematical model describing spatial-temporal dynamics of virus spread. The radius of the
plaque over time was fitted by the mathematical model. Based on estimated parameters, we
quantified these VSV in terms of the basic reproduction number, which is an index for virus
spread. Our analysis revealed that P424A amino acid mutations in Ebola GP and D508N in
Marburg GP reduced the binding to GP most effectively. In addition, our simulations based on
the mathematical model could reproduce virus amplification and merging of plaque as we
actually observed in plaque assay. Based on our findings, it may be possible to design antivirals
that efficiently block the filovirus entry according to the importance of amino acid mutations.
REFERENCES
[1] You, L., & Yin, J. (1999). Amplification and spread of viruses in a growing plaque. Journal of theoretical
biology, 200(4), 365-373.
[2] Haseltine, E. L., Lam, V., Yin, J., & Rawlings, J. B. (2008). Image-guided modeling of virus growth and
spread. Bulletin of mathematical biology, 70(6), 1730.
2019 한국수리생물학회 62 2019.06.20(목) - 6.22(토)
Complex synchronization of a ring-structured network of
FitzHugh-Nagumo neurons with single- and dual-state gap
junctions under ionic gates and external electrical disturbance
Malik Muhammad Ibrahim and Il Hyo Jung
Department of Mathematics, Pusan National University
Synchronization plays an essential role in processing information and decisions by neurons
and their networks in the brain, and it is useful to study the synchronization of neuron networks,
as part of the process of understanding the functionality of both healthy and diseased brains. In
the past, most studies had developed control schemes relating to synchronization problems
which were limited to two or three neurons, which cannot depict the dynamic synchronization
behavior of neuron networks. In this work, we investigated the synchronization issues
associated with a ring-structured network of FitzHugh–Nagumo (FHN) neurons, under external
electrical stimulation, and with single- and dual-state gap junctions. In addition, gap junctions
(coupling)s and ionic gate disturbances were included in the dynamics of this FHN neuronal
network, making our work both more realistic, and more challenging. Thus, each neuron in this
network was influenced synaptically by its neighboring two neurons. A simple, robust, adaptive
control scheme, for both a single- and dual-gap-junction network, has been proposed, which
will compensate for the nonlinear dynamics, without direct cancelation, to achieve
synchronization. Sufficient conditions to guarantee synchronization of both membrane
potentials and recovery variables were derived, by using Lyapunov stability theory. Finally, the
proposed scheme was validated, and its efficacy was comprehensively analyzed through
numerical simulations.
REFERENCES
[1] Ibrahim, M. M., & Jung, H. (2019). Complex synchronization of a ring-structured network of FitzHugh–
Nagumo neurons with single-and dual-state gap junctions under ionic gates and external electrical
disturbance. IEEE Access.
2019 한국수리생물학회 63 2019.06.20(목) - 6.22(토)
A mathematical model for the management of Plasmodium vivax
malaria endemic in South Korea with realistic distributions of
incubation and relapse
Sungchan Kim1, Jong Hyuk Byun2 and Il Hyo Jung1,2
1. Department of Mathematics, Pusan National University
2. Finance · Fishery · Manufacture Industrial Mathematics Center on Big Data, Pusan
National University
Correspondence should be addressed to Il Hyo Jung; [email protected]
Some previous studies aimed to highlight that, when developing models for public health
use, we need to pay careful attention to the intrinsic assumptions embedded within classical
frameworks. In this talk, we develop a renewal model to capture the dynamics of P. vivax
malaria with realistic distributions of incubation and relapse. Finally, we will show the potential
effect of new drug, named “Tafenoquine”, which get rid of remained dormant in the liver, in
the eradication of malaria endemic using the model.
REFERENCES
[1] Cox, D. R. (2017). The theory of stochastic processes. Routledge.
[2] Mundasad, S. (23 July 2018). New drug for recurring malaria, Global Health Correspondent, BBC News
(web-site: https://www.bbc.com/news/health-44801139)
[3] Lover, A. A., Zhao, X., Gao, Z., Coker, R. J., & Cook, A. R. (2014). The distribution of incubation and
relapse times in experimental human infections with the malaria parasite Plasmodium vivax. BMC
infectious diseases, 14(1), 539.
2019 한국수리생물학회 64 2019.06.20(목) - 6.22(토)
Strategic dynamics analysis of smoking and smoking substitute
through evolutionary game theory
Jae Hun Jung
Department of Mathematics, Pusan National University
Smoking is a social problem with behavioral addiction. In recent years, the number of people
using smoking substitutes such as e-cigarettes and IQOS has increased dramatically, and there
is no accurate scientific evidence on its health-related issues, but it does harm people who do
not smoke. Now, game dynamics model how individuals and populations change their
strategies over time with payoffs comparisons, but what is considered is then the fitness of the
individual which depends on the strategy of others. Using the evolutionary game theory, we
will construct a model of how people's smoking behaviors change by applying to smoke and
smoking substitutes.
REFERENCES
[1] SMITH, John Maynard. Evolution and the Theory of Games. Cambridge university press, 1982.
[2] BROOM, Mark; RYCHTÁ R, Jan. Game-theoretical models in biology. CRC Press, 2013.
[3] BAUCH, Chris T.; EARN, David JD. Vaccination and the theory of games. Proceedings of the National
Academy of Sciences, 2004, 101.36: 13391-13394.
[4] POLETTI, Piero, et al. Spontaneous behavioral changes in response to epidemics. Journal of theoretical
biology, 2009, 260.1: 31-40.
2019 한국수리생물학회 65 2019.06.20(목) - 6.22(토)
Session D1
Ecological Modeling: monitoring, assessment, and
management for ecosystems
Organizer: 박영석 (경희대학교)
Date/Time: 6월 22일(토) 10:00
Speakers:
1. 차윤경 (서울시립대학교)
2. 김진우 (부경대학교)
3. 정유리 (부경대학교)
4. 이경은 (생태와미래지식인협동조합)
5. 배미정 (국립낙동강생물자원관)
6. 이대성 (경희대학교)
7. 김동균 (전남대학교)
2019 한국수리생물학회 66 2019.06.20(목) - 6.22(토)
Development of a Predictive Bayesian network Model for Application
to the Alert System for Cyanobacterial Blooms of South Korea
YoonKyung Cha1, * , Sunghyun Yoon1, Hyeongchul Jeon1, Young-Seuk Park2, and Joong-Hyuk Min3
1 Department of Environmental Engineering, University of Seoul, Seoul, Republic of Korea
2 Department of Biology, Kyung Hee University, Seoul, Republic of Korea
3 Water Environment Research Department, National Institute of Environmental Research, Incheon, Republic
of Korea
A Bayesian network (BN) model was developed for application to the Alert System for
Cyanobacterial Blooms of South Korea. The threshold values of four alert levels correspond to
harmful cyanobacteria cell counts exceeding 1,000, 10,000, and 1,000,000 per milliliter,
respectively. The different alert levels were predicted using a variety of environmental factors.
The complex, stochastic nature of the relationships between cyanobacterial blooms and
influencing environmental factors indicate that machine learning methods, such as the BN, may
be one of the suitable approaches for the prediction purpose. The BN, having the advantage of
visualization and ease of communication, has been widely applied in numerous fields of
science and engineering. The classification tree (CART) method was used for predictor
selection and discretization, and the sensitivity analysis was used for prioritizing predictor
importance. The monitoring data for cyanobacteria cell counts and environmental factors were
collected on a weekly basis from May to November in 2018 along the 16 weirs across the four
major rivers. The predictor candidates included meteorological variables (mean daily
temperature, minimum daily temperature, maximum daily temperature, mean daily wind speed,
daylight hour, daily precipitation, and mean daily water temperature), water quality variables
(pH, DO, BOD, COD, TSS, TN, TP, electrical conductivity, and chlorophyll-a), mean daily
flow, and the alert level itself. In the model structure, one-week time lag was assumed between
the changes in environmental factors and the consequent responses in cyanobacterial blooms.
As a result of the combined CART and sensitivity analyses, daylight hour, water temperature,
flow, and the alert level one-week prior to the current level were selected as predictors in a
decreasing order of importance. The model performance evaluated using test data (20% of total
data) was generally acceptable with the accuracy of 0.63 and the area under curve (AUC) of
0.81, 0.71, 0.84, and 0.02 for the Alert Levels 1 to 4, respectively. The low AUC for the Alert
Level 4 resulted from the rare occurrence (2 out of 625) of cyanobacterial blooms with such
severity.
2019 한국수리생물학회 67 2019.06.20(목) - 6.22(토)
Evolvement of a length-based model: its application to Korean
chub mackerel (Scomber japonicus) stock
Jinwoo Gim1, Saang-Yoon Hyun1* and Jae Bong Lee2
1Department of Marine Biology, Pukyong National University
2Coastal Water Fisheries Resources Research Division, National Institute of Fisheries Science
Under circumstances that data are not available on ages of fish sampled by a fishery or survey,
we have to resort to a size-based model especially when time series data about fish body sizes
are provided. Assessment of Korean chub mackerel (Scomber japonicus) stock was in such
a case. Evolving Quinn’s size-based model (Quinn et al. 1998), we assessed Korean chub
mackerel stock. The merits of Quinn’s size-based model lied in making an ‘imaginary’ age-
structure of a fish population and being able to estimate year- and age-population sizes along
cohorts. Our data were yield and lengths of fish caught by a large purse seine fishery from
2000 - 2017, and catch-per-unit-effort from 1996 - 2017. We evolved Quinn’s model in three
ways. First, we modified the objective function as the residual sum of squares in Quinn’s
model into the negative log-likelihood function where the distributions of the annual length
data and yield data were assumed to follow a multinomial and a log-normal, respectively.
Second, we applied a prior distribution for natural mortality as opposed to using a fixed value
in Quinn’s model. Third, using the optimization software, AD model builder, we estimated
not only point estimates of parameters but also the uncertainty in those estimates. Estimates
of annual biomass (including recruits) ranged from 1.24 x 106 MT to 2.58 x 106 MT.
Estimates of fishing mortality rates were the range of 0.10 - 0.27 year -1 while estimate of
natural mortality was 0.13 year-1.
2019 한국수리생물학회 68 2019.06.20(목) - 6.22(토)
Application of a Bayesian state-space production model to
assessment of Korean chub mackerel (Scomber japonicus) stock
Yuri Jung1, Saang-Yoon Hyun1*, and Young Il Seo2
1*Department of Marine Biology, Pukyong National University
2Coastal Water Fisheries Resources Research Division, National Institute of Fisheries Science
*Corresponding author: [email protected]
State-space model have been desired for stock assessment because they incorporate
variabilities in population dynamics and observation. Recently, the models were expanded
with Bayesian approach, which updates information on parameters with data and prior
knowledge. In this study, we aimed to assess chub mackerel (Scomber japonicus) stock using
a Bayesian state-space model. We chose a surplus production model given available data,
which are annual yield and catch-per-unit-effort (CPUE) from 1999 to 2017. We included
process errors and observation errors in the model to depict uncertainties in the model structure
and measurement on CPUE data. While adding process errors would improve realism that
the model describes, high dimensional integration is required to estimate many parameters.
We implemented the model in software ADMB-RE that fit the model using the Laplace
approximation. We also introduced prior distributions to stabilize the numerical integration,
then we obtained posterior samples from ADMB-RE using a Markov Chain Monte Carlo
algorithm. Applying the state-space surplus production model to fishery data on mackerel,
we inferred model parameters as well as management benchmarks. Comparison between the
management references and the predicted annual biomass suggested the stock suffered
overexploitation in the years of 1999-2017. Our results should aid in setting management
strategies on mackerel stock.
2019 한국수리생물학회 69 2019.06.20(목) - 6.22(토)
Spatial Patterns of Benthic Macroinvertebrate Communities
KyoungEun Lee1, Gyu-Suk Kwak1, Yong-Hyuck Jang1, and Tae-Soo Chon1,2
1Ecology and Future Research Association
2Division of Biological Sciences (Prof. Emer.), Pusan National University
Stream communities respond to natural and anthropogenic disturbances in a complex manner.
Objective analyses of community responses are required to predict and manage biodiversity in
ecosystems safely and sustainably. Benthic macroinvertebrate communities in streams were
collected by the Surber sampler in the Nakdong River in the southern peninsula of Korea.
Community abundances across different orders of streams were patterned by Geographical
SOM (Geo-SOM). Metacommunity cluster were formed according to topography and
anthropogenic impacts based on the Geo-SOM, consisting of large (50 km – 120 km) and small
(20 km – 50 km) zones. Subsequently the clustered communities were analyzed by beta-
diversities and rank abundance distributions (RADs). According to beta diversities inter-
community characteristics including nestedness and spatial turnover were accordingly
presented in association with linear and water-course distances between the sample sites. RADs
presented the impacts of disturbances on community structure effectively. Feasibility of
dimension extension applied to point-data is further discussed in prediction and sustainable
management of stream meta-communities.
2019 한국수리생물학회 70 2019.06.20(목) - 6.22(토)
Evaluating the status of freshwater biodiversity in upper-middle
basin in Nakdong River, Korea
Mi-Jung BAE
Biodiversity Research Team, Nakdonggang National Institute of Biological Resources
We evaluated the freshwater biodiversity based on benthic macroinvertebrate in the upper
and middle basin, Nakdong River basin in South Korea. We surveyed benthic
macroinvertebrate and environmental factors in 110 sampling sites mainly in headwater
streams from 2016 to 2018. Sampling sites included various small river basin as well as various
anthropogenic disturbances (e.g., abandoned mined area, industrial area, agricultural area,
natural area, etc). Self-Organizing Map (SOM), indicator species analysis (IndVal) and random
Forest (RF) were applied to figure out the relationship between environmental factors and
benthic macroinvertebrate community. Geographical factors including altitude were the main
environmental factors to determine benthic macroinvertebrate community. The influential
environmental factors to influence the distribution of benthic macroinvertebrate species
extracted from IndVal were different based on RF
2019 한국수리생물학회 71 2019.06.20(목) - 6.22(토)
자료 기반 모델을 이용한 담수어류 분포 특성 분석 및 예측
이대성 1, 민중혁 2, 박영석 1
1경희대학교 생물학과, 2국립환경과학원 물환경연구부
지속 가능한 생태계의 구성 및 관리를 위해서는 생태계 내 다양한 환경 인자와 생물 사이의 상
호 작용을 이해하고, 환경 변화에 대한 생물의 반응을 예측할 필요가 있다. 본 연구에서는 지속적
인 모니터링을 통해 얻은 담수 어류 자료를 바탕으로 환경과 어류 종간 상호관계 및 국내 주요
수계에서 주요 어류 종의 서식지 특성을 분석하였다. 또한 random forest 모델을 이용하여 주요 종
에 대해 분포 및 서식지 특성을 평가하는 자료 기반 모델을 작성하였다. 분석 및 모델에는 환경
부 및 국립환경과학원에서 수행하는 생물측정망 자료를 사용하였다. 어류는 국내 서식하는 주요
종으로 서로 다른 서식지 특성을 보이는 피라미, 참갈겨니, 돌고기, 배스, 블루길 등 5종을 선택하
였으며, 각 조사지점에서 측정된 수리수문적, 기후적, 지리적, 및 이화학적 환경 인자를 사용하였
다. 연구 결과, random forest 모델의 정확도 및 AUC 값은 0.85 및 0.91로 높았으며, 주요 어류 종에
대해 하천차수, 수폭, 평균기온 등의 물리적, 기후적 요소 및 BOD, T-N과 같은 수질 요소가 중요
함을 확인하였다. 또한 유속의 증감에 대한 주요 어류 종의 반응을 평가한 결과, 대다수의 지역에
서 배스와 블루길은 유속이 감소함에 서식 확률이 증가하였으며, 반면 피라미, 참갈겨니, 돌고기
는 감소하였다.
2019 한국수리생물학회 72 2019.06.20(목) - 6.22(토)
Biological Integrity and Ecosystem Regime Shift
Dong-Kyun Kim and Ihn-Sil Kwak
Fisheries Science Institute, Chonnam National University
In this talk, we present ecosystem behaviors in response to the status of biological integrity.
In the context of resistance and resilience of ecosystem, we introduce two characteristics of
ecosystem behaviors: (i) nonlinear regime shift, and (ii) time lag of system recovery (also
known as hysteresis). We demonstrate several examples of the ecosystem behaviors associated
with changes of external stress. It is remarkable that the tipping points of regime shift vary
along the status of biological integrity. Hence, this information offers new insights into
ecosystem restoration and management.
2019 한국수리생물학회 73 2019.06.20(목) - 6.22(토)
Session D2
Mathematical Approaches to Epidemic Models and
Interacting Systems
Organizer: 이효정 (Hokkaido University)
Date/Time: 6월 22일(토) 10:00
Speakers:
1. Hyojung Lee (Hokkaido University)
2. Yoon-gu Hwang (Yonsei University)
3. Taeyong Lee (Yonsei University)
4. Jin-Hyeon Kim (Korea University)
5. Yunjeong Lee (Yonsei University)
2019 한국수리생물학회 74 2019.06.20(목) - 6.22(토)
Estimating the congenital rubella syndrome accounting for
asymptomatic infection using serological data in Japan
Hyojung Lee, Taishi Kayano and Hiroshi Nishiura
Graduate School of Medicine, Hokkaido University
Rubella is a vaccine-preventable disease caused by rubella virus. Although most of rubella
infections are asymptomatic or mild, it leads to pregnancy complications, including congenital
rubella syndrome (CRS) when pregnant women are infected especially during the first trimester
of pregnancy. A major epidemic of rubella occurred in Japan from 2012-2014, reporting a total
of 12,614 rubella cases and 45 CRS cases. Unfortunately, another major epidemic has been
ongoing since August 2018. We estimated congenital rubella syndrome (CRS) infections, using
an integral equation based on age-specific incidence of rubella among adult women, the time
delay from gestational age of infection to diagnosis of CRS, and distribution of the mothers’
age at delivery. We used epidemic data during 2012–2014 to parameterize the model and
applied this in the prediction for 2018–2019. However, this study did not take into account
asymptomatic infection. Therefore, analyzing the seroprevalence data by age and prefecture to
quantify the asymptomatic infection, we aim to improve our estimates of the CRS case more
accurately.
REFERENCES
[1] H. Lee, T. Kayano and H. Nishiura, Predicting congenital rubella syndrome in Japan, 2018-2019,
International Journal of Infectious Diseases, 82, 1-5 (2019)
[2] T. Kayano, H. Lee and H. Nishiura, Modelling supplementary vaccination program of rubella using the
2012-13 epidemic data in Japan, International Journal of Environmental Research and Public Health, 16(8),
1473 (2019).
2019 한국수리생물학회 75 2019.06.20(목) - 6.22(토)
Feedback control problem of an SIR epidemic model based on the
Hamilton-Jacobi-Bellman equation
Yoon-gu Hwang, Jeehyun Lee, and Hee-dae Kwon
Department of Computational Science & Engineering, Yonsei University
In epidemiology, data is often non-reproducible, incomplete and experiments are usually
impossible. This gives great importance to mathematical models as a possible tool to evaluate
the effect of control measures and to assist in the formulation of policy decision. In this research,
we consider open and feedback controls applied to deterministic model and stochastic models,
respectively.
The baseline problem is open control of deterministic SIR model, which is extended to
capture characteristics of epidemics. Feedback control is employed to reflect the status of
susceptible and infectious individuals when a control measure to be implemented. While
Pontryagin's maximum principle is a typical approach for the open control, Bellman's principle
is one for feedback control. It converts the control problem to a non-linear first order partial
differential equation from which an optimal solution is obtained.
On the other hand, it is challenging to estimate the initial values of SIR model due to
measurement errors and lack of information. Also, the contact rate involves a high level of
uncertainty caused by biological factors. Therefore, it is reasonable to introduce variability,
which is formulated as random variables in the model. To this end, we consider how to obtain
optimal control of SIR model with random inputs. We apply the polynomial of chaos
techniques to solve the optimal control problem involving random variables.
REFERENCES
[1] Yves Achdou et al. Hamilton-Jacobi equations: approximations, numerical analysis and applica- tions. Vol. 10.
Springer, 2013.
[2] Linda JS Allen. “An introduction to stochastic epidemic models”. In: Mathematical epidemiology. Springer,
2008, pp. 81–130.
[3] Michael G Crandall and Pierre-Louis Lions. “Viscosity solutions of Hamilton-Jacobi equations”. In:
Transactions of the American mathematical society 277.1 (1983), pp. 1–42.
[4] Suzanne Lenhart and John T Workman. Optimal control applied to biological models. CRC Press, 2007.
[5] S Wang, F Gao, and KL Teo. “An upwind finite-difference method for the approximation of viscos- ity
solutions to Hamilton-Jacobi-Bellman equations”. In: IMA Journal of Mathematical Control and Information 17.2
(2000), pp. 167–178.
[6] Jiongmin Yong and Xun Yu Zhou. Stochastic Controls. Hamiltonian Systems and HJB Equations. New York,
NY: Springer Science & Business Media, 1999.
2019 한국수리생물학회 76 2019.06.20(목) - 6.22(토)
Optimization on PDE Model of the Multiple-Coated Oncolytic
Viruses and Cancer Cells
Taeyong Lee1,*, Adrianne L. Jenner3, Peter S. Kim3, and Jeehyun Lee1,2
1Department of Mathematics, College of Science, Yonsei University, Seoul, Korea.
2Department of Computer Science & Engineering, Yonsei University, Seoul, Korea. 3School of Mathematics and Statistics, University of Sydney, Sydney, Australia.
Among various type of therapies for treating cancer, virotherapy is a promising method which
utilizes the ability of viruses to destroy cancer cells. While this approach has been successful
in some applications, there are still issues to be addressed. Due to the immunity to viruses, the
proper concentration of viruses is not maintained. One way to overcome this difficulty is to
coat the viruses with PEG(Polyethylene glycol), which enables them to evade the immunity.[2]
However, coated viruses are less infectious, which may deteriorate the efficacy of the
virotherapy.[1,2] Therefore, we consider optimal treatment protocols for oncolytic viruses
striking a balance between evading the immunity and maintaining efficacy. We describe the
interaction between a growing tumor and a coated virus using a system of partial differential
equations. Then we employ the control theory to determine how many levels of coating and
what proportion of each level are desirable to result in the least volume of tumor.
REFERENCES
[1] Jenner, A. L., Yun, C. O., Kim, P. S., & Coster, A. C. (2018). Mathematical modelling of the interaction between
cancer cells and an oncolytic virus: insights into the effects of treatment protocols. Bulletin of mathematical
biology, 80(6), 1615-1629.
[2] Kim, P. H., Sohn, J. H., Choi, J. W., Jung, Y., Kim, S. W., Haam, S., & Yun, C. O. (2011). Active targeting and
safety profile of PEG-modified adenovirus conjugated with herceptin. Biomaterials, 32(9), 2314-2326.
2019 한국수리생물학회 77 2019.06.20(목) - 6.22(토)
Effect of Cooperation in Two-Species Microbial System
Jin-Hyeon Kim and Kwang-Il. Goh
Department of physics, Korea University
We study a two-species interacting particle system as a model for the emergence of
multicellularity in microbial systems. In our model, each species behaves like the one in the
contact process (CP) except for additional cooperative interactions between species which
represent a division of labor. First, we present the mean-field approximation of the model as a
tool for the study of the qualitative features. Next, we perform extensive Monte Carlo
simulations of the model in (1+1)-dimension. From the results of the mean-field theory and
Monte Carlo simulations, we construct the phase diagram and find the conditions that co-
existence of both species is predominant and maintained. Also, both methods show that there
are two types of phase transitions. The first type is an absorbing phase transition which occurs
from a fluctuating active phase into an absorbing state. Besides, the model displays another
phase transition from a segregated domain phase into a mixed domain phase depending on the
cooperation constant. When the cooperation effect is weak, the system is dominated by the
segregated single-species domains. In this case, each species lives separated from the other by
a well-defined boundary. On the other hand, when the cooperation effect is strong enough, the
mixed-species domain emerges, within which both species live and mingle together. Within
such domain, different species cells tend to locate adjacent to each other and effectively behave
like bi-cellular organisms. We characterize these two types of phase transitions and critical
phenomena from the perspective of non-equilibrium phase transition.
2019 한국수리생물학회 78 2019.06.20(목) - 6.22(토)
A Mixed Effect Model for HIV Dynamics
Yunjeong Lee, Jeehyun Lee and Hee-dae Kwon
Department of Computational Science and Engineering, Yonsei University
In this talk, we introduce a hierarchical nonlinear mixed effect model for HIV. Our goal is to
develop a model to account for variations at both the individual and population levels. The first
step to achieve this goal is to estimate parameters at individual level applying least squares
method and find ranks of parameters using sensitivity analysis. Then, we perform model
reduction by generating nested models according to the ranks so that less computational efforts
are needed. Finally, the joint distributions of individual specific parameters across the
population are obtained based on global two-stage method. The proposed model, involving
variability among patients, is able to predict future patterns of the response for a new patient
and to design individual treatment therapy regimes.
REFERENCES
[1] B. M. Adams, H. T. Banks, M. Davidian, H.-D. Kwon, H. T. Tran, S. N. Wynne, and E. S. Rosenberg, HIV
Dynamics: Modeling, Data Analysis, and Optimal Treatment Protocols, J. Comput. Appl. Math., 184(1):10-49
(2005)
[2] H. T. Banks, S. Hu, and W. C. Thompson, Modeling and Inverse Problems in the Presence of Uncertainty,
Monographs and Research Notes in Mathematics, Taylor and Francis, Hoboken, NJ (2014)
[3] H. T. Banks and M. L. Joyner, AIC under the Framework of Least Squares Estimation, Appl. Math. Lett., 74,
33-45 (2017)
[4] M. Davidian, Nonlinear Models for Repeated Measurement Data, Routledge (2017)
[5] B. F. Lund, H. E. Berntsen, and B. A. Foss, Methods for Parameter Ranking in Nonlinear, Mechanistic Models,
IFAC Proceedings Volumes, 38(1):578-583 (2005)
2019 한국수리생물학회 79 2019.06.20(목) - 6.22(토)
Poster Session
2019 한국수리생물학회 80 2019.06.20(목) - 6.22(토)
2019 한국수리생물학회 81 2019.06.20(목) - 6.22(토)
Mathematical modeling of the 2016-2017 the Republic
of Korea HPAI epidemic and the optimal strategies
considering spatial heterogeneity
Youngsuk Ko 1, Jonggul Lee2 and Eunok Jung 1 1) Department of Mathematics, Konkuk University, Seoul 05029, KOREA
2) National Institute for Mathematical Sciences, Daejeon 34047, KOREA
Corresponding Author: Eunok Jung, [email protected]
Highly pathogenic avian influenza (HPAI) subtype H5N6 caused outbreak in the Republic
of Korea since November 16, 2016. More than 40 million of poultry were slaughtered and that
caused serious economic loss. In this study, we considered the sixteen towns sixteen towns,
which are administrative divisions of Eumseong-gun and Jincheon-gun. We devised spatial-
temporal model for the HPAI outbreak of chicken and duck farms and adopted two types of
culling (pre-emptive and infective premises) as a function, respectively. With Next-generation
method, we calculated local reproductive number of each town as risk factor. We focused on
pre-empative culling and set the culling area of each town as control to minimize farm loss. By
applying optimal control theory into our model, we found that pre-emptive culling is necessary
for the towns with high-reproductive number otherwise it is not. We present optimal controls
of each town under different conditions and model results.
REFERENCES
[1] van den Driessche P, “Reproduction numbers of infectious disease models”, Infectious
Disease Modelling, 2017, 2-288.
[2] Gulbudak H, Martcheva M, “Forward hysteresis and backward bifurcation caused by
culling in an avian influenza model”, Mathematical Biosciences, 2013, 202-212.
[3] Kang Y, Shen X, Yuan R, Xiang B, Ren T, “Pathogenicity and transmissibility of
three avian influenza A (H5N6) viruses isolated from wild birds”, Journal of Infection. 2018, 76-286.
[4] Jung E, Iwami S, Takeuchi Y, Jo Tc, “Optimal control strategy for prevention of avian
influenza pandemic,” Journal of Theoretical Biology. 2009, pp. 260-220.
2019 한국수리생물학회 82 2019.06.20(목) - 6.22(토)
Role of OCT1 in regulation of miR-451-LKB1-AMPK-OCT1-
mTOR core signaling network and cell invasion in glioblastoma
Donggu Lee , Yangjin Kim, Junho Lee, and Sean Lawler
Department of Mathematic, Konkuk University
Glioblastoma (GBM) is the most aggressive form of brain cancer with the short median
survival time. GBM is characterized by the hallmarks of aggressive proliferation and critical
cellular infiltration. miR-451 and their downstream molecules (LKB1, AMPK, OCT1, mTOR)
are known to play a pivotal role in regulation of the balance of proliferation and aggressiv
e invasion in response to metabolic stress in a tumor microenvironment (TME). Recent studies
show that Oct1 and LKB1 plays a significant role in regulation of the mutual inhibition betwe
en cell proliferation and migration. In this work, we develop a mathematical model of signaling
pathway dynamics in GBM evolution with particular focus on the relative balance of
proliferation capacity and invasion potential. In the present work we represent the
miR-451451/LKB1/AMPK/OCT1/mTOR pathway by a system of ordinary differential
equations and show how the effects of fluctuating glucose on tumor cells need to be
reprogrammed by taking into account the recent history of glucose variations and
an AMPK/LKB1/miR-451/Oct1 reciprocal feedback loop.
REFERENCES
[1] Y. Kim, J. Lee, D. Lee, and H.G. Othmer, Synergistic Effects of Bortezomib-OV Therapy and Anti
-Invasive
Strategies in Glioblastoma: A Mathematical Model, Cancers, 11(2), E215 (2019)
[2] Y. Kim, H. Kang, G. Powathil, H. Kim, D. Trucu, W. Lee, S. Lawler, and M. Chaplain, Role of extracellular
matrix and microenvironment in regulation of tumor growth and LAR-mediated invasion in glioblastoma,
PLoS One, 13(10), e0204865 (2018)
[3] Y. Kim, J. Yoo, T. Lee, J. Liu, J. Yu, M.A. Caligiuri, B. Kaur, and A. Friedman, Complex Role of NK cells
in regulation of OV-Bortezomib therapy, Proc Natl Acad Sci, 115(19), 4927-4932, (2018)
[4] Y. Kim, H. Kang, and S. Lawler, The Role of the miR-451-AMPK Signaling Pathway in Regulation of Cell
Migration and Proliferation in Glioblastoma, in `Mathematical Models of Tumor-Immune System Dynamics’,
Springer Proceedings in Mathematics & Statistics, Springer, New York, 107, 125-155 (2014)
[5] Y. Kim, H. Jeon, and H. Othmer, The role of the tumor microenvironment in glioblastoma: A mathematical
model, IEEE Trans Biomed Eng, 64(3), 519-527 (2017)
2019 한국수리생물학회 83 2019.06.20(목) - 6.22(토)
Synergistic Effects of Bortezomib-OV Therapy and Anti-
Invasive Strategies in Glioblastoma: A Mathematical Model
Junho Lee, Yangjin Kim, Donggu Lee and Hans G. Othmer
Department of Mathematics, Konkuk University
It is well-known that the tumor microenvirment (TME) plays an important role in the
regulation of tumor growth and the efficacy of anti-tumor therapies. Recent studies have
demonstrated the potential of combination therapies, using oncolytic viruses (OVs)
in conjunction with proteosome inhibitors for the treatment of glioblastoma, but the role of the
TME in such therpies has not been studied. In this paper, we develop a mathematical model
for combination therapies based on the proteosome inhibitor bortezomib and the oncolyt
ic herpes simplex virus (oHSV), with the goal of understanding their roles in bortezomib-
induced endoplasmic reticulum (ER) stress, and how the balance between apoptosis and
necroptosis is affected by the treatment protocol. We show that the TME plays a significant
role in anti-tumor efficacy in OV combination therapy, and illustrate the effect of different
spatial patterns of OV injection. The results illustrate a possible phenotypic switch within
tumor populations in a given microenvironment, and suggest new anti-invasion therapies.
REFERENCES
[1] Yangjin Kim, Ji Young Yoo, Tae Jin Lee, Joseph Liu, Jianhua Yu, Michael A Caligiuri, Balveen Kaur, a
nd Avner Friedman, Complex Role of NK cells in regulation of OV-Bortezomib therapy, PNAS (2018)
[2] Yangjin Kim, Hyejin Jeon, and Hans Othmer, The role of the tumor microenvironment in glioblastoma:
A mathematical model, IEEE Trans Biomed Eng (IF 2.347), 64(3):519-527, March 2017.
[3] Yoo J, et al. (2014) Bortezomib-induced unfolded protein response increases oncolytic hsv-
1 replication resulting in synergistic antitumor effects. Clin Cancer Res 20(14):3787–3798.
[4] Yoo J, et al. (2016) Bortezomib treatment sensitizes oncolytic hsv-treated tumors to nk cell immunotherapy.
Clin Cancer Res pii: clincanres.:1003.2016
2019 한국수리생물학회 84 2019.06.20(목) - 6.22(토)
Strong competition model with non-uniform dispersal in a
heterogeneous environment
Wonhyung Choi and Inkyung Ahn
Department of Mathematics, Korea University
In this study, a strong competition model was considered between two species in a
heterogeneous environment. For a system with two different constant diffusion rates for each
competitor, the fast diffuser can be selected evolutionally under suitable assumptions if the
competing interaction between the species is strong. We also claim that a strongly interacting
competition leads to a more evolutionary selection than that with the same population dynamics
if a species moves with a certain non-uniform dispersal. Furthermore, species with a certain
non-uniform dispersal have a competitive advantage over linear random diffusers. In addition,
a species with highly sensitive dispersal response to the environment may survive. These
strongly competitive advantages were demonstrated by investigating the stability of semi-
trivial solutions of the system with non-uniform dispersal and comparing it to the conditions
of the model with constant diffusion.
2019 한국수리생물학회 85 2019.06.20(목) - 6.22(토)
The effect of dispersal toward fitness for predators with
predation-induced dispersal
Kwangjoong Kim, Wonhyung Choi and Inkyung Ahn
College of General Education, Kookmin University
Department of Mathematic, Korea University
[email protected], [email protected]
In many cases, one may observe that the dispersal of living organism is affected by the
circumstance of the environment in which they reside. In particular, we will consider
predator’s dispersal, called a predation-induced dispersal (PID), which represents the
change in predator’s motility depending on the difference between the maximal predation
rate and the death rate of predators in a region. In this presentation, to understand how PID
affects the fitness of species in a heterogeneous region, we examine predator-prey models
with ratio-dependent functional responses under no-flux boundary conditions where the
predators move according to the PID. We conclude that a non-uniform dispersal (PID) of
predators in response to their given heterogeneous environment increases fitness of the
predator; thus the predators with PID can invade with increased probability when rare, even
in the case where the predator with linear dispersal can invade a certain region.
2019 한국수리생물학회 86 2019.06.20(목) - 6.22(토)
Blood Flow in Catheterized Artery: Numerical Study
Shama Javeed1
, Jung Il Hyo1
1 Department of Mathematics, Pusan National University, Busan, Korea
Corresponding Author: Shama Javeed1
The evolution of coronary balloon angioplasty has increased the use of various sizes cathete
rs in the arteries during the recent years. In the present study, pulsatile blood flow through
catheterized artery is analyzed by the flow modeling of two immiscible fluids. The fluid flow
in the primary region is treated as non-Newtonian power law fluid while, the fluid flow in
peripheral region is categorized as Newtonian fluid. The catheter inside the vessel is treated as
rigid body of small radius. The resulting system of differential equations that represents th
evelocity profiles of the respective fluids are solved numerically by finite difference metho
d.Additionally, the results of velocity profiles with different physical quantities are analyzed
by numberical method and ANSYS-Fluent simulations for the purposes of a comprehensive
summary of blood flow through catheterized artery.
REFERENCES
[1] Back L.H., “Estimated mean flow resistance increase during coronary artery catheterization”, Journal of
Biomechanics, 27, pp.169–175 (1994). PMID:8132684.
[2] Sankar D.S., Hemalatha K., “Pulsatile flow of Herschel–Bulkley fluid through catheterized arteries–
A mathematical model”, Applied Mathematical Modeling, 31,pp.1497–1517(2007).
[3] Yilmaz F., Gundogdu M.Y., “Acritical review on blood flow in large arteries; relevance to blood rheology,
viscosity models, and physiologic conditions”, Korea-Australia Rheology Journal, 20,pp.197– 211(2008).
[4] Zuhaila Ismail, Ilyani Abdullah, Norzieha Mustapha, Norsarahaida Amin, The power law model of blood
flow through a tappered overlaping stenosed
[5] artery, Appl. Math. Comput. 195 (2008) 669–680.
[6] M. Anand and K. R. Rajagopal, A model for the formation and lysis of blood clots, Pathophysiol. Haemost.
Thromb. 34 (2005), 109–120.
[7] J. C. Misra and B. K. Sahu, Flow through blood vessels under the action of a periodic acceleration filed,
Comput. Math. Appl. 16 (1988), 993–1016.
[8] M. Sajid, A. Zaman, N. Ali, A. M. Siddiqui, “Pulsatile flow of blood in a vessel using an Oldroyd-B fluid,
Inter. J. of Nonlinear Sci. and Numerical Simulation, Volume 16, (2015) 197-206.
2019 한국수리생물학회 87 2019.06.20(목) - 6.22(토)
NASH(Nonalcoholic steatohepatitis) control: Nrf1 and
microRNA-378 form a double negative feedback model
Sieun Lee
Department of Mathematics, Kyungpook National University
Nonalcoholic steatohepatitis(NASH) is one of the severe form of non-alcoholic fatty liver
disease(NAFLD). NASH is a crucial stage for pathogenesis of hepatocellular cancer.
microRNA-378(miR-378) is a small RNA that plays an important role in the regulation of lipid
and energy homeostasis. Recent research show that miR-378 inhibition has strong therapeutic
potential for NASH. And NAFLD have a negative feedback loop between miR-378 and
Nrf1(Nuclear receptor factor 1). Thus We developed ODE model using those experimental
results of the paper and investigated the effectiveness of miR-378 inhibition therapy by
predicting NASH.
REFERENCES
[1] Zhang T, Zhao X, Steer CJ, Yan G, Song G “A negative feedback loop betweenmicroRNA-378 and Nrf1
promotes the development of hepatosteatosis in mice treatedwith a high fat diet” Methabolism Clinical and
Experimaental, 87-96 (2018)
[2] Zhang T “MicroRNA-378 promotes hepatic inflammation and fibrosis via modulation of the NF-B-TNF pathway” Journal of hepatology, 183-191 (2019)
2019 한국수리생물학회 88 2019.06.20(목) - 6.22(토)
Effects of climate change on malaria transmission dynamics
Yongin Choi, James Slghee Kim, Jung Eun Kim, Chang Hyeong Lee
Department of Mathematical Sciences, Ulsan National Institute of Science and Technology (UNIST),
Ulsan, Republic of Korea
Malaria is a vector-borne disease transmitted by female Anopheles mosquitoes and the
Plasmodium vivax (P. vivax) - one of malaria parasites and a primary pathogen in South Korea.
It is known that the life cycle of mosquitoes is highly sensitive to climate factors such as
temperature and precipitation.
Based on the actual incidence data in South Korea, we develop a malaria transmission model
with climate-dependent parameters. This research represents that climate change caused by
global warming has affects the pattern of malaria outbreak expanding the endemic regions. We
investigate the potential risk of malaria outbreaks through the computation of seasonal
reproduction number and vectorial capacity under RCP scenarios. Furthermore, we have
investigated the effect of controls on immature mosquitoes, adult mosquitoes, and humans.