1. Bioinformatics for Stem Cell Lecture 1 Debashis Sahoo, PhD

2. Outline Introduction History of Bioinformatics Introduction to computing Data collection Experiment design Data analysis

3. Bioinformatics Definition Biological Data – Representation – Storage – Access – Processing bi·o·in·for·mat·ics [bahy-oh-in-fer-mat-iks] – noun ( used with a singular verb ) the retrieval and analysis of biochemical and biological data using mathematics and computer science, as in the study of genomes.

4. http://www.merriam-webster.com/dictionary/bioinformatics http://www.ncbi.nlm.nih.gov/About/primer/bioinformatics.html

6. The science behind Michael Levitt's Nobel Prize Michael Levitt, PhD, has dramatically advanced the field of structural biology by developing sophisticated computer algorithms to build models of complex biological molecules.

7. “It is hard for me to say confidently that, after fifty more years of explosive growth of computer science, there will still be a lot of fascinating unsolved problems at peoples' fingertips, that it won't be pretty much working on refinements of well-explored things. I can't be as confident about computer science as I can about biology. Biology easily has 500 years of exciting problems to work on, it's at that level.” Professor Donald E. Knuth The "father" of the analysis of algorithms He is the author of the seminal multi-volume work The Art of Computer Programming.

8. HISTORICAL PERSPECTIVE

9. History of Bioinformatics Gergor Mendel (1866, Verhandlungen des naturforschenden Vereins Brünn) 1951 – structure for the alpha-helix and beta-sheet – Pauling and Corey (PNAS – 1951) 1953 - double helix model for DNA – Watson and Crick (Nature, 171: 737-738, 1953) 1955 – protein sequence of bovine insulin – F. Sanger.

10. History of Bioinformatics 1958 – 1990 – Revolution in Computer Science and Engineering Computer, email, network, internet 1990 – BLAST – Altschul, S.F., Gish, W., Miller, W., Myers, E.W. & Lipman, D.J. (1990) "Basic local alignment search tool." J. Mol. Biol. 215:403-410. 1995 - The Haemophilus influenzea genome (1.8 Mb) is sequenced. 1993 – 2013 – Microarrays 2005 – 2013 – High-throughput sequencing

11. INTRODUCTION TO COMPUTING

12. What is a computer? 10010110 Controller Read/Write head Tape Turing Machine (1936) Alan Turing, "On computable numbers, with an application to the Entscheidungsproblem", Proceedings of the London Mathematical Society, Series 2, 42 (1937), pp 230–265.

13. Modern Computer ProcessorMain MemoryDisk Drives IO controller DisplayKeyboardMouse

14. What is a Computer Program? Executable file Load to Memory Run the program C ProgramAssembly Program

15. DATA COLLECTION

16. Public Databases Gene Expression Omnibus (GEO) Array Express National Center for Biotechnology Information (NCBI) UCSC Genome Browser The human protein atlas Catalogue of Somatic Mutations in Cancer – COSMIC The Cancer Genome Atlas (TCGA)

17. http://www.ncbi.nlm.nih.gov/geo/

18. http://www.ebi.ac.uk/arrayexpress

19. http://www.ncbi.nlm.nih.gov/pubmed

20. http://genome.ucsc.edu

21. http://www.proteinatlas.org/

22. http://www.sanger.ac.uk/genetics/CGP/cosmic/

23. https://tcga-data.nci.nih.gov/tcga/

24. EXPERIMENT DESIGN

25. To call in the statistician after the experiment is done may be no more than asking him to perform a postmortem examination : he may be able to say what the experiment died of. - R. A. Fisher

26. http://graphpad.com/guides/prism/5/ user-guide/prism5help.html

27. Independent Samples Statistical tests are based on the assumption that each subject was sampled independently. Provides maximum amount of information. Provides better estimation of the mean.

28. The Gaussian Approximation Everybody believes in the normal approximation, the experimenters because they think it is a mathematical theorem, the mathematicians because they think it is an experimental fact. G. Lippman (1845 – 1921)

29. Sample Size Estimation

30. DATA ANALYSIS

31. Correlation

32. Hypothesis Testing Randomly select samples from the population State the null hypothesis – Distribution of values in two different populations are the same Perform the statistical test – T test, F test, Chi-sq test Get P-value – Set a threshold (usually < 0.05) for significance

33. Multiple Comparisons The Bonferroni correction – P < 0.05/N (N = number of comparisons) False Discovery Rate (FDR) – Q value – What fraction of all the discoveries are false? – Q = 10%, N = 100, smallest p-value < Q/N – http://genomics.princeton.edu/storeylab/qvalue/ – Permutation based approaches