1 / 42

Introduction to Bioinformatics 236523

Introduction to Bioinformatics 236523. Lecturer: Dr. Yael Mandel-Gutfreund Teaching Assistance: Shula Shazman Sivan Bercovici. Course web site : http://webcourse.cs.technion.ac.il/236523. What is Bioinformatics?. Course Objectives. To introduce the bioinfomatics discipline

alayna
Download Presentation

Introduction to Bioinformatics 236523

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Introduction to Bioinformatics236523 Lecturer: Dr. Yael Mandel-Gutfreund Teaching Assistance: Shula Shazman Sivan Bercovici Course web site : http://webcourse.cs.technion.ac.il/236523

  2. What is Bioinformatics?

  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 explainin general how they work (limitation etc..)

  4. Course Structure and Requirements • Class Structure • 2 hours Lecture • 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 and submitted in pairs

  5. Grading • 20 % Homework assignments • 80 % final project

  6. Literature list • Gibas, C., Jambeck, P. Developing Bioinformatics Computer Skills. O'Reilly, 2001. • Lesk, A. M. Introduction to Bioinformatics. Oxford University Press, 2002. • 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 MITPress, 2004

  7. What is Bioinformatics?

  8. What is Bioinformatics? “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.

  9. 21ST centaury Genome Transcriptome Proteome Central Paradigm in Molecular Biology Gene (DNA) mRNA Protein

  10. from purely lab-based science to an information science Bioinformatics Bio = Informatics

  11. From DNA to Genome First protein sequence Watson and Crick DNA model 1955 1960 First protein structure 1965 1970 1975 1980 1985

  12. 1990 First bacterial genome Hemophilus Influenzae 1995 Yeast genome First human genome draft 2000

  13. Complete Genomes Total 1117 706456 Eukaryotes 119 7843 Bacteria 929 578383 Archaea 69 5029 2009 20082007

  14. 1117 genomes What’s Next ? The “post-genomics” era Annotation Comparative genomics Structural genomics Functional genomics Goal: to understand the living cell

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

  16. Identify the genes within a given sequence of DNA Identify the sites Which regulate the gene Annotation Predict the function

  17. 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…

  18. promoter TF binding site Transcription Start Site Ribosome binding Site ORF=Open Reading Frame CDS=Coding Sequence CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATGCAA TATGGACAATTGGTTTCTTCTCTGAAT ................................. ..............TGAAAAACGTA

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

  20. Comparative genomics

  21. Perhaps not surprising!!! How humans are chimps? Comparison between the full drafts of the human and chimp genomes revealed that they differ only by 1.23%

  22. So where are we different ?? Human ATAGCGGGGGGATGCGGGCCCTATACCC Chimp ATAGGGG - - GGATGCGGGCCCTATACCC Mouse ATAGCG - - - GGATGCGGCGC -TATACCA

  23. And where are we similar ??? VERY SIMAILAR Conserved between many organisms VERY DIFFERENT

  24. Functional genomics

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

  26. From the gene expression pattern we can lean: What does the gene do ? When is it needed? What other genes or proteins interact with it? ….. What's wrong??

  27. Structural Genomics

  28. protein complexes Evolutionary relationship fold Biologic processes Protein-ligand complexes Shape and electrostatics Active sites Functional sites The protein three dimensional structure can tell much more then the sequence alone

  29. Resources and Databases The different types of data are collected in database • Sequence databases • Structural databases • Databases of Experimental Results All databases are connected

  30. Sequence databases • Gene database • Genome database • Disease related mutation database • ………….

  31. Genome Browsers Easy “walk” through the genome

  32. Genome Browsers • UCSC Genome Browserhttp://genome.ucsc.edu/ • Ensembl Genome Browser(http://www.ensembl.org) • WormBase:http://www.wormbase.org/ • AceDB:http://www.acedb.org/ • Comprehensive Microbial Resource:http://www.tigr.org/tigr-scripts/CMR2/CMRHomePage.spl • FlyBase:http://flybase.bio.indiana.edu/

  33. Mutation database • Single base difference in a single position among two different individuals of the same species • Play an important role in differentiation and disease

  34. Sickle Cell Anemia • Due to 1 swapping an A for a T, causing inserted amino acid to be valine instead of glutamine in hemoglobin Image source: http://www.cc.nih.gov/ccc/ccnews/nov99/

  35. Healthy Individual >gi|28302128|ref|NM_000518.4| Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

  36. Diseased Individual >gi|28302128|ref|NM_000518.4| Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GGTGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTPVEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

  37. Structure Databases • 3-dimensional structures of proteins, nucleic acids, molecular complexes etc • 3-d data is available due to techniques such as NMR and X-Ray crystallography

  38. Databases of Experimental Results • Data such as experimental microarray images- gene expression data • Proteomic data- protein expression data • Metabolic pathways, protein-protein interaction data, regulatory networks • ETC………….

  39. PubMed Literature Databases http://www.ncbi.nlm.nih.giv/PubMed Service of the National Library of Medicine

  40. Putting it all Together • Each Database contains specific information • Like other biological systems also these databases are interrelated

  41. PROTEIN PIR SWISS-PROT DISEASE LocusLink OMIM OMIA ASSEMBLED GENOMES GoldenPath WormBase TIGR MOTIFS BLOCKS Pfam Prosite GENOMIC DATA GenBank DDBJ EMBL ESTs dbEST unigene GENES RefSeq AllGenes GDB SNPs dbSNP GENE EXPRESSION Stanford MGDB NetAffx ArrayExpress PATHWAY KEGG COG STRUCTURE PDB MMDB SCOP LITERATURE PubMed

More Related