1. An overview of Bioinformatics

2. Cell and Central Dogma

3. Source: “Post-genome Informatics” by M Kanehisa

5. Deduction and Analogy

6. Biological System (Organism) Reductionistic Synthetic Approach (Experiments) (Bioinformatics) Building Blocks (Genes/Molecules) Source: “Post-genome Informatics” by M Kanehisa

7. Principles Known Physics Chemistry Biology Matter Compound Organism Elementary Elements Genes Particles Yes Yes No Source: “Post-genome Informatics” by M Kanehisa

8. Searching and learning problems in biology Source: “Post-genome Informatics” by M Kanehisa

9. Sequence Comparison: Algorithms and Approaches

10. Homology Search New sequence Similar sequences Expert knowledge Sequence interpretation Sequence database (Primary data) retrieval Source: “Post-genome Informatics” by M Kanehisa

11. Pairwise sequence alignment by dynamic programming Needleman Wunsch alogrithm Source: “Post-genome Informatics” by M Kanehisa

12. Database Search for Similar Sequences

13. Web Lab

14. Motif

15. Source: “Introduction to Protein Structure” by Branden & Tooze

16. Web Lab

17. Motif Search New sequenceExpert knowledge Sequence interpretation Sequence database (Primary data) Motif library (Empirical rules) inference Source: “Post-genome Informatics” by M Kanehisa

18. Introduction to Structural Biology Structural Biology

19. Source: “Introduction to Protein Structure” by Branden & Tooze

21. Web Lab

24. Genome Project

26. Web Lab

27. Genome Sequencing and Genome Annotation

28. A general model of the structure of genomic sequences Source: “Bioinformatics” by D W Mount

29. Microarray

30. Joe Sutliff for Science 291 p1224 (2001) What kind of solution Genomics can provide with ?  High Throughput Gene Discovery

31.  165 genes are up-regulated in 75% tumors (MAPK pathway, APC, promotion of mitosis; 69 unknown)  170 genes are down-regulated in 65% tumors (hepatocyte-specific gene products, retinoid metabolism; 75 unknown)  Hierarchical Clustering  K-means  Self Organization Map  Support Vector  Single Value Decomposition

32. Gene Expression andTranscriptome

35. Web Lab

36. Proteomicsand Functional Genomics

37. Source: “Post-genome Informatics” by M Kanehisa

38. Web Lab

39. Integrative Genomics

41. Network of physical interactions between nuclear proteins

42. Attributes of generic network structures

44. Virtual Cell Living Cell Perturbation Environmental change Gene disruption Gene overexpression Dynamic Response Changes in: Gene expression profiles, Etc. Biological Knowledge Molecular and Cellular Biology,Biochemistry, Genetics, etc Basic Principles Practical Applications Complete Genome Sequences Source: “Post-genome Informatics” by M Kanehisa

45. Take Home Message  Define the biological problem.  Why is bioinformatics important ? A synthesis approach.  Prediction is a dangerous game. Always try your best to validate in the bench side.  The devil is in the detail. Always try different bioinformatic tools and databases.  Your knowledge rests on your own practice.

46. Reference Books you will find useful: Bioinformatics -sequence and genome analysis by D W Mount Introduction to Bioinformatics by A M Lesk Post-genome Informatics by M Kanehisa

47. Evolution of molecular biology databases Database category Data contentExamples 1. Literature databaseBibliographic citationsMEDLINE(1971) On-line journals 2. Factual DatabaseNucleic acid sequencesGenBank(1982) Amino acid sequencesEMBL(1982) 3D molecular structuresDDBJ(1984) SWISS_PROT(1986) PDB(1971) 3. Knowledge baseMotif librariesPROSITE(1988) Molecular classificationSCOP(1994) Biochemical pathwaysKEGG(1995)