1. Introduction to Bioinformatics Lecturer: Prof. Yael Mandel-Gutfreund Teaching Assistance: Rachelly Normand Edward Vitkin Course web site : http://webcourse.cs.technion.ac.il/236523

2. 2 What is Bioinformatics?

3. 3 Course Objectives To introduce the bioinfomatics discipline To make the students familiar with the major biological questions which can be addressed by bioinformatics tools To introduce the major tools used for sequence and structure analysis and explain in general how they work (limitation etc..)

4. 4 Course Structure and Requirements 1.Class Structure 1.2 hours Lecture 2.1 hour tutorial 2. Home work Homework assignments will be given every second week The homework will be done in pairs. 5/5 homework assignments will be submitted 2. A final project will be conducted in pairs * Project will be presented as a poster –poster day 19.3

5. 5 Grading 20 % Homework assignments 80 % final project (10% proposal, 20% supervisor evaluation 70% poster presentation)

6. 6 Literature list Mount, D.W. Bioinformatics: Sequence and Genome Analysis. 2nd ed.,Cold Spring Harbor Laboratory Press, 2004. Advanced Reading Jones N.C & Pevzner P.A. An introduction to Bioinformatics algorithms MIT Press, 2004

7. 7 What is Bioinformatics?

8. 8 “The field of science in which biology, computer science, and information technology merge to form a single discipline” Ultimate goal: to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned. What is Bioinformatics?

9. 9 Central Paradigm in Molecular Biology mRNAGene (DNA)Protein 21 ST centaury GenomeTranscriptomeProteome

10. 10 From DNA to Genome Watson and Crick DNA model 1955 1960 1965 1970 1975 1980 1985

11. 11 1995 1990 2000 First human genome draft First genome Hemophilus Influenzae Yeast genome

12. 12 Total 1379 294 Eukaryotes 133 39 Bacteria 1152 235 Archaea 94 23 Complete Genomes 2010 2005 Total complete genomes 10.10.13 = 7381

13. 1,000 Genomes Project: Expanding the Map of Human Genetics Researchers hope the effort will speed up the discovery of many diseases's genetic roots 13

14. 14 Main Goal: To understand the living cell AnnotationComparative genomics Functional genomics 25000 genomes… What’s Next ? The “post-genomics” era Systems Biology

15. And beyond… Personalized medicine 15

16. From ….25000 genomes To…Understanding living cells

17. 17 CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATG CAA TAT GGA CAA TTG GTT TCT TCT CTG AAT.................... TGAAAAACGTA Annotation

18. 18 Annotation Identify the genes within a given sequence of DNA Identify the sites Which regulate the gene Predict the function What do they do???

19. 19 How do we identify a gene in a genome? A gene is characterized by several features (promoter, ORF…) some are easier and some harder to detect…

20. 20 Using Bioinformatics approaches for Gene hunting Relative easy in simple organisms (e.g. bacteria) VERY HARD for higher organism (e.g. humans)

21. 21 Comparative genomics

22. 22 Comparison between the full drafts of the human and chimp genomes revealed that they differ only by 1.23% How can we be so similar--and yet so different? How humans are chimps? Perhaps not surprising!!!

23. 23 Where are we different ?? Where are we similar ??? VERY SIMAILAR Conserved between many organisms VERY DIFFERENT

24. 24 Human ATAGCGGGGGGATGCGGGCCCTATACCC Chimp ATAGGGG--GGATGCGGGCCCTATACCC Mouse ATAGCG---GGATGCGGCGC-TATACC-A Human ATAGCGGGGGGATGCGGGCCCTATACCC Chimp ATAGGGGGGATGCGGGCCCTATACCC Mouse ATAGCGGGATGCGGCGCTATACCA Sometime minor changes in critical genes can make a big difference

25. 25 Single change in a genes among humans can be responsible for sever diseases Sickle Cell Anemia Due to 1 swapping of an A for a T Image source: http://www.cc.nih.gov/ccc/ccnews/nov99/

26. 26 Healthy Individual >gi|28302128|ref|NM_000518.4| Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GG A GAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTP E EKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

27. 27 Diseased Individual >gi|28302128|ref|NM_000518.4| Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GG T GAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTP V EKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

28. 28 Functional genomics

29. 29 TO BE IS NOT ENOUGH In any time point a gene can be functional or not

30. The difference in the brain size between Human and apes is mainly related to the different levels of the genes expression and not their content

31. 31 Systems Biology

32. Jeong et al. Nature 411, 41 - 42 (2001) Biological networks

33. What can we learn from Biological Networks Is the protein essential for the organism ? Is it a good drug targets? What can we learn about this protein

34. How can bioinformatics contribute to Medicine? http://www.tedmed.com/talks/show?id=17961 34

35. What of all this will we learn in the course? 35 The course will concentrate on the bioinformatics tools and databases which are used to : - Annotate genes, - Compare genes and genomes - Infer the function of the genes and proteins - Analyze the interactions between genes and proteins ETC….

36. 36 Main Topics 1. Introduction to bioinformatics 2. Pairwise alignment 3. Database search 4. Protein alignments 5. MSA and phylogenetic analysis 6. Sequencing 7. Motif search-function prediction 8. Gene expression 9. Structural bioinformatics (proteins and RNA) 10. Biological networks