bioinformatics lab 陳博現 老師 吳謂勝 博二生 陳泓竹 碩二生 林立協 劉家榮...

Bioinformatics Lab 陳博現 老師 吳謂勝 博二生 陳泓竹 碩二生

林立協 劉家榮 張文杰 碩一生

執行計畫• 國科會 基因體醫學國家型科技計畫• 統計模型與訊號處理在蛋白質酵素功能活性部位偵測上之應用

Bioinformatics

• a new emerging interdisciplinary research area

• interface between biological and computational sciences

(math, ee, cs,…)

• computational management of all kinds of biological information

Biological information is hierarchical in nature

• DNA mRNA protein protein

interactions informational pathways

informational networks cells tissues

or networks of cells an organism

populations ecologies

Research topics

• DNA level:

DNA sequence alignment; gene prediction;

gene evolution;…

• RNA level:

gene expression study; transcription mechanism; post-transcription modification;…

• Protein level: protein 2D, 3D structure prediction; protein active site pre

diction; protein-protein interactions; protein-DNA interactions;…

• System level: (pathways, networks) Genome 基因體學 (gene-gene interactions) ex. use gene chips to study gene regulatory network

Proteome 蛋白體學 (protein-protein interactions) ex. use protein chips to study protein interaction network

Microarray

• a kind of gene chips

• record the gene expression profiles (in time series) of the whole genome

• with large amount of biological information imbedded

• need to develop data mining methodology to extract this biological information

112/04/18

Principle of Microarray

在 slide 上點上已知的單股 DNA片段 (probe), 做成檢驗用的 slide 。

取得待檢的單股 cDNA(target), 並標示螢光染劑放在 slide 上和 probe 作用。

使用螢光顯微鏡觀察染色的情形。

Printing

Hybridization

Scanning

Analysis 分析染色的 pattern 便可進一步研究待檢DNA/RNA 的資訊。

傳統方法 基因晶片

見樹不見林 見樹又見林

大海撈針 一網打盡

下一代生物晶片 (3D)

•多功能•高靈敏度•較易檢測及操作•可重複使用

研發成功後可廣泛應用於 :•癌症研究、診斷、治療•高血壓、糖尿病、老化等複雜症狀之研究•快速之各種病毒感染檢測

史丹福大學

清華大學

清華特色

光電

微機電

生技生化

國立清華大學

分子生醫光電實驗室基因晶片及新型生物晶片之研發與應用

20,100 點 在 2 cm x 2 cm

Affymetrix GeneChip

Analysis

Microarray data

Gene expression profiles

Construct the gene regulatory network

• cells regulate their gene expression during development or in response to the change of the environment

• use the expression profiles of the yeast cell cycle (about 6,000 genes) as data sets

• develop computational algorithms to construct the gene regulatory network

Requirement of students

• preliminary courses: genetics, biological database, introduction to microarray, statistics, …

• weekly meeting to present bio-related papers

• be familiar with Matlab software package

• wish to do bioinformatics research in your master career