Introduction to Bioinformatics 236523

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Introduction to Bioinformatics236523

• Lecturer Dr. Yael Mandel-Gutfreund
• Teaching Assistance
• Shula Shazman
• Sivan Bercovici

Course web site http//webcourse.cs.technion.ac.
il/236523
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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
mRNA
Gene (DNA)
Protein
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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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1990
First bacterial genome Hemophilus Influenzae
1995
Yeast genome
First human genome draft
2000
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Complete Genomes
Total 1117 706 456 Eukaryotes
119 78 43 Bacteria 929 578 383
Archaea 69 50 29
2009 2008 2007
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The post-genomics era
1117 genomes Whats Next ?
Annotation
Comparative genomics
Structural genomics
Functional genomics
Goal to understand the living cell
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Annotation
CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG CGTGCAA
ATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA CTTTGTTACGCGT
TTTTGTCATGGCTTTGGTCCCGCTTTGTTC AGAATGCTTTTAATAAGCG
GGGTTACCGGTTTGGTTAGCGAGA AGAGCCAGTAAAAGACGCAGTGACG
GAGATGTCTGATG CAA TAT GGA CAA TTG GTT TCT TCT CTG
AAT ...... .............. TGAAAAACGTA
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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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CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG CGTGCAA
ATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA CTTTGTTACGCGT
TTTTGTCATGGCTTTGGTCCCGCTTTGTTC AGAATGCTTTTAATAAGCG
GGGTTACCGGTTTGGTTAGCGAGA AGAGCCAGTAAAAGACGCAGTGACG
GAGATGTCTGATG 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
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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 (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/

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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 http//www.cc.nih.gov/ccc/ccnews/nov
99/
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Healthy Individual

• gtgi28302128refNM_000518.4 Homo sapiens
  hemoglobin, beta (HBB), mRNA
• ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACC
  ATGGTGCATCTGACTCCTGA
• GGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAG
  TTGGTGGTGAGGCCCTGGGC
• AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGG
  GGATCTGTCCACTCCTGATG
• CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGT
  GCCTTTAGTGATGGCCTGGC
• TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACT
  GTGACAAGCTGCACGTGGAT
• CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCA
  TCACTTTGGCAAAGAATTCA
• CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAAT
  GCCCTGGCCCACAAGTATCA
• CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCC
  CTAAGTCCAACTACTAAACT
• GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAA
  CATTTATTTTCATTGC
• gtgi4504349refNP_000509.1 beta globin Homo
  sapiens
• MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLS
  TPDAVMGNPKVKAHGKKVLG
• AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFG
  KEFTPPVQAAYQKVVAGVAN
• ALAHKYH

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Diseased Individual

• gtgi28302128refNM_000518.4 Homo sapiens
  hemoglobin, beta (HBB), mRNA
• ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACC
  ATGGTGCATCTGACTCCTGA
• GGTGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAG
  TTGGTGGTGAGGCCCTGGGC
• AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGG
  GGATCTGTCCACTCCTGATG
• CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGT
  GCCTTTAGTGATGGCCTGGC
• TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACT
  GTGACAAGCTGCACGTGGAT
• CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCA
  TCACTTTGGCAAAGAATTCA
• CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAAT
  GCCCTGGCCCACAAGTATCA
• CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCC
  CTAAGTCCAACTACTAAACT
• GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAA
  CATTTATTTTCATTGC
• gtgi4504349refNP_000509.1 beta globin Homo
  sapiens
• MVHLTPVEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLS
  TPDAVMGNPKVKAHGKKVLG
• AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFG
  KEFTPPVQAAYQKVVAGVAN
• 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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(No Transcript)
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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 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