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Introduction to Bioinformatics 236523
Lecturer: Dr. Yael Mandel-Gutfreund Teaching Assistance: Shula Shazman Sivan Bercovici Course web site :
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What is Bioinformatics?
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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..)
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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
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Grading 20 % Homework assignments 80 % final project
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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 MIT Press, 2004
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What is Bioinformatics?
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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.
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Central Paradigm in Molecular Biology
Gene (DNA) mRNA Protein 21ST centaury Genome Transcriptome Proteome
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from purely lab-based science to an information science
Bioinformatics Bio = Informatics
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From DNA to Genome First protein sequence Watson and Crick DNA model
1955 1960 First protein structure 1965 1970 1975 1980 1985
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First bacterial genome
1990 First bacterial genome Hemophilus Influenzae 1995 Yeast genome First human genome draft 2000
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Complete Genomes 2009 2008 2007 Total 1117 706 456
Eukaryotes Bacteria Archaea
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The “post-genomics” era
1117 genomes What’s Next ? The “post-genomics” era Annotation Comparative genomics Structural genomics Functional genomics Goal: to understand the living cell
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Annotation CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG
CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATG CAA TAT GGA CAA TTG GTT TCT TCT CTG AAT TGAAAAACGTA
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Annotation Identify the genes within a given sequence of DNA
Identify the sites Which regulate the gene Annotation Predict the function
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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…
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promoter TF binding site Transcription Start Site
Ribosome binding Site ORF=Open Reading Frame CDS=Coding Sequence Transcription Start Site CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATG CAA TAT GGA CAA TTG GTT TCT TCT CTG AAT TGAAAAACGTA
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Using Bioinformatics approaches for Gene hunting
Relative easy in simple organisms (e.g. bacteria) VERY HARD for higher organism (e.g. humans)
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Comparative genomics
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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%
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So where are we different ??
Human ATAGCGGGGGGATGCGGGCCCTATACCC Chimp ATAGGGG - - GGATGCGGGCCCTATACCC Mouse ATAGCG GGATGCGGCGC -TATACCA
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And where are we similar ???
VERY SIMAILAR Conserved between many organisms VERY DIFFERENT
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Functional genomics
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TO BE IN NOT ENOUGH In any time point a gene can be functional or not
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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??
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Structural Genomics
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The protein three dimensional structure can tell much more then the sequence alone
protein complexes Biologic processes fold Evolutionary relationship Shape and electrostatics Active sites Protein-ligand complexes Functional sites
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Resources and Databases
The different types of data are collected in database Sequence databases Structural databases Databases of Experimental Results All databases are connected
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Sequence databases Gene database Genome database
Disease related mutation database ………….
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Genome Browsers Easy “walk” through the genome
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Genome Browsers UCSC Genome Browser http://genome.ucsc.edu/
Ensembl Genome Browser ( WormBase: AceDB: Comprehensive Microbial Resource: FlyBase:
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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
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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:
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Healthy Individual >gi| |ref|NM_ | Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi| |ref|NP_ | beta globin [Homo sapiens] MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH
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Diseased Individual >gi| |ref|NM_ | Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GGTGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi| |ref|NP_ | beta globin [Homo sapiens] MVHLTPVEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH
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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
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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………….
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PubMed Literature Databases http://www.ncbi.nlm.nih.giv/PubMed
Service of the National Library of Medicine
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Putting it all Together
Each Database contains specific information Like other biological systems also these databases are interrelated
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PROTEIN DISEASE ASSEMBLED GENOMES GENOMIC DATA ESTs GENES SNPs
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
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