1. Computers and Programming for Biologists

2. What is Bioinformatics? The use of information technology to collect, analyze, and interpret biological data. An ad hoc collection of computing tools that are used by molecular biologists to manage research data. –Computational algorithms –Database schema –Statistical methods –Data visualization tools

3. The Human Genome Project

4. A Genome Revolution in Biology and Medicine  We are in the midst of a "Golden Era" of biology  The Human Genome Project has produced a huge storehouse of data that will be used to change every aspect of biological research and medicine  The revolution is about treating biology as an information science, not about specific biochemical technologies.

5. The job of the biologist is changing –The biologist will spend more time using computers & on experimental design and data analysis (and less time doing tedious lab biochemistry) –Biology will become a more quantitative science (think how the periodic table affected chemistry) As more biological information becomes available and laboratory equipment becomes more automated...

6. What are the Tools? Alignment Similarity = string matching –Pattern search –Hash tables and substitution matrices Clustering Genome assembly and annotation

7. Align by hand GATGCCATAGAGCTGTAGTCGTACCCT < — — > CTAGAGAGC- GTAGTCAGAGTGTCTTTGAGTTCC Somebody should make a computer program for this kind of thing…

8. Global vs. Local Alignments

9. BLAST Algorithm

10. >ZFISH9:GNL-TI fi72b02.y1 Length = 724 Score = 307 bits (786), Expect = 8e-82 Identities = 145/200 (72%), Positives = 166/200 (82%), Gaps = 1/200 (0%) Frame = +3 Query: 45 VLLKEYRVILPVSVDEYQVGQLYSVAEASKNXXXXXXXXXXXXXXPYEK-DGEKGQYTHK 103 +L+KE+R++LPVSV+EYQVGQLYSVAEASKN PYEK DGEKGQYTHK Sbjct: 123 MLIKEFRIVLPVSVEEYQVGQLYSVAEASKNETGGGDGVEVLKNEPYEKEDGEKGQYTHK 302 Query: 104 IYHLQSKVPTFVRMLAPEGALNIHEKAWNAYPYCRTVITNEYMKEDFLIKIETWHKPDLG 163 IY LQSKVP+FVR+LAP AL IHEKAWNAYPYCRTV+TNEYMK++FLI IETWHKPDLG Sbjct: 303 IYRLQSKVPSFVRLLAPSSALIIHEKAWNAYPYCRTVLTNEYMKDNFLIMIETWHKPDLG 482 Query: 164 TQENVHKLEPEAWKHVEAVYIDIADRSQVLSKDYKAEEDPAKFKSIKTGRGPLGPNWKQE 223 QENVH L+ E WK VE ++IDIADRSQV +KDYK +EDPA FKS KTGRGPLGP+WK+E Sbjct: 483 EQENVHNLDSERWKQVEVIHIDIADRSQVDTKDYKPDEDPATFKSQKTGRGPLGPDWKKE 662 Query: 224 LVNQKDCPYMCAYKLVTVKF 243 L ++DCP+MCAYK VTV F Sbjct: 663 LPQKRDCPHMCAYKXVTVNF 722

12. Clustering (Phylogenetics)

13. Genome Assembly

14. Raw Genome Data:

15. UCSC

16. The Challenge of New Data Types Gene expression microarrays –thousands of genes, imprecise measurements –huge images, private file formats Proteomics –high-throughput Mass Spec –protein chips: protein-protein interactions Genotyping –thousands of alleles, thousands of individuals

17. cDNA spotted microarrays

19. High-Throughput Genotyping

20. Bioinformatics: Beyond Using Websites You can do a lot of sophisticated bioinformatics using public websites But at some point you may be faced with a LOT of data - thousands of searches, annotations, etc. The only solution is to have your own bioinformatics computer, database, and custom programs. Needs more processor power and more hard drive space than a typical desktop personal computer

23. Bioinformatics Requires Powerful Computers One definition of bioinformatics is "the use of computers to analyze biological problems.” As biological data sets have grown larger and biological problems have become more complex, the requirements for computing power have also grown. Computers that can provide this power generally use the Unix operating system - so you must learn Unix be a computational biologist

24. Stable and Efficient Unix is very stable - computers running Unix almost never crash Unix is very efficient it gets maximum number crunching power out of your processor (and multiple processors) it can smoothly manage extremely huge amounts of data it can give a new life to otherwise obsolete Macs and PCs Most new bioinformatics software is created for Unix - its easy for the programmers

25. Open Source Bioinformatics Almost all of the bioinformatics software that you need to do complex analyses is free for UNIX computers The Open Source software ethic is very strong among biologists –Bioinformatics.org –Bioperl.org –Open-bio.org New algorithms generally appear first as free software (a publication requirement)

26. Free Software Linux operating system, mySYQL database Perl - programming language Blast and Fasta - similarity search Clustal - multiple alignment Phylip - phylogenetics Phred/Phrap/Consed - sequence assembly and SNP detection EMBOSS - a complete sequence analysis package created by the EMBL (like GCG)

27. Computer Hardware is not Free However, you can build a powerful Linux cluster for $20-50K (depending on how much power you need) The real cost is for a person to manage the machines, install the software, and train scientists to use it. Small schools can join together or affiliate with a larger neighbor.

28. Do Biologists have to become Programmers? No, but it can give you a big advantage. More and more of biology is becoming computer aided design of experiments, automated equipment, and computational analysis of the results. “I just want to say one word to you... Databases”

29. Why teach bioinformatics in undergraduate education?  Demand for trained graduates from the biomedical industry  Bioinformatics is essential to understand current developments in all fields of biology  We need to educate an entire new generation of scientists, health care workers, etc.  Use bioinformatics to enhance the teaching of other subjects: genetics, evolution, biochemistry

30. Genomics in Medical Education “The explosion of information about the new genetics will create a huge problem in health education. Most physicians in practice have had not a single hour of education in genetics and are going to be severely challenged to pick up this new technology and run with it." Francis Collins

31. Becoming a Unix Power User Learn more Unix commands Use the shell to execute simple programs Write scripts - automate repetitive tasks Download and install the latest bioinformatics software Drive your system manager crazy… or get your own Unix machine (Linux on an Intel machine or Mac OS-X)

32. BioPerl Why re-invent the wheel? Lots of common bioinformatics tasks have already been programmed as “modules” in Perl. –Grab sequences from GenBank, extract e- values and annotation from Blast results, etc. Download from www.bioperl.org

33. Resources Notes for Lincoln Stein’s course on “Genome Informatics” http://stein.cshl.org/genome_informatics/index.html BioPerl.org http://bio.perl.org/ PERL for biologists (Kurt Stüber) http://caliban.mpiz-koeln.mpg.de/~stueber/perl/ “Why Biologists Want to Program Computers” by James Tisdall: http://www.oreilly.com/news/perlbio_1001.html

34. Resources for Bio-Computing

35. Stuart M. Brown, Ph.D. stuart.brown@med.nyu.edu www.med.nyu/rcr Bioinformatics: A Biologist's Guide to Biocomputing and the Internet Essentials of Medical Genomics