1. Introduction of bioinformatics and Biological Database 高雄醫學大學 生物醫學暨環境生物學系 助理教授 張學偉 2006/08/08

2. Outline  Fields of Bioinformatics  Genome Projects Today  Database issue in “Nucleic Acids Research”  Server issue in “Nucleic Acids Research”

3. Post-Genomic Era: Lots of Data!

4. “The study of genetic and other biological information using computer and statistical techniques.” A Genome Glossary, Science, Feb 16, 2001

5. Bioinformatics  Bioinformatics is the discipline of biology that has evolved to gather, store and manage in specialized databanks the vast amounts of biological data, which it then mines for knowledge

6. 生物資訊的領域 資料庫的建立 與整合 序列分析 結構 / 功能 分析 實驗資料分析知識管理 ref. 中央研究院計算中心通訊 Vol.19 No.20 生物資訊學

7. Biotech and Computer Science 1953 1958 1974 1981 1990 1992 2003 Watson and Crick DNA double helix discovery Computer revolution begin Stan Cohen and Herb Bover recombinant DNA molecule First portable computer begin Human genome project begin World web site Human genome fully mapped Breaking point of Biotechnology The breaking point of Biotechnology is Human Genome Project GenBank GCG Package

8. Bioinformatics- hot issues  Genome Analysis Pipeline Analysis Genome Annotation SNP  Data warehouse/ Databases integration  New Algorithm  Literature Mining  System Biology/ Microarray Analysis

9. The growth of Genbank (updates) Prediction: data size doubles every 14 months 44,575,745,176 bases, from 40,604,319 reported sequences (up to Dec.,15, 2004)

10. Biological databases  Like any other database Data organization for optimal analysis  Data is of different types Raw data (DNA, RNA, protein sequences) Curated data (DNA, RNA and protein annotated sequences and structures, expression data)

11. The growth of public domain bio-databases (The Molecular Biology Database Collection from Nucleic Acids Research)

12. “The Gene Ontology (GO) project seeks to provide a set of structured vocabularies for specific biological domains that can be used to describe gene products in any organism.” A few key points: GO is a “structured” vocabulary, which is really a specialized type of a “controlled” vocabulary. Gene Ontology database

13.  The ontologies in GO are intended to describe three biological areas, “molecular function”, “biological processes” and “cellular components”.  GO was originally developed through the collaboration of the members of three model organism projects: SGD, the Saccharomyces Genome database; FlyBase, the Drosophila genome database; and MGD/GXD, the Mouse Genome Informatics databases.

14. What GO is Not 1. GO is not a way to unify biological databases. Sharing nomenclature is a step toward unification, but is not, in itself, sufficient. 2. GO is not a dictated standard, mandating nomenclature across databases. Groups participate because of self-interest and cooperate to arrive at a consensus. 3. GO does not define homologies between gene products from different organisms. The use of the GO results in shared annotations for gene products from different organisms, and this may reflect an evolutionary relationship, but the shared annotation is in itself not sufficient for such a determination.

15. Swimming in Data Sources

16. Database Integration