Introduction to Bioinformatics Victor Jin

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Introduction to Bioinformatics Victor Jin Department of Biomedical Informatics Ohio State University

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Transcript of Introduction to Bioinformatics Victor Jin

Page 1: Introduction to Bioinformatics Victor Jin

Introduction to Bioinformatics

Victor JinDepartment of Biomedical Informatics

Ohio State University

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What is Bioinformatics?

bio·in·for·mat·ics

: the collection, classification, storage, and analysis of biochemical and

biological information using computers especially as applied in molecular

genetics and genomics.

Source: Merriam-Webster's Medical Dictionary, © 2002 Merriam-Webster, Inc.

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Myth1 : Bioinformatics is about genomics

• Nucleotide – DNA, RNA, …• Genome – Sequences, chromosomes, expressed data, …• Protein – Sequences, 3-D structure, interaction, …• System – Gene network, protein network, TFs, …• Other – Masspec, microarray, images, lab records, journals, literatures, …

The goal is to understand how the system works.

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Myth2 : Data vs. Information

Data

Nucleotide – DNA, RNA, …Genome – Sequences, chromosomes, expressed data, …Protein – Sequences, 3-D structure, interaction, …System – Gene network, protein network, TFs, …Other – Masspec, microarray, images, lab records, journals, literatures, …

Information

GenotypePhenotypeGenotype-Phenotype relationshipSNPs PathwaysDrug targets

Getting data is “easy”, extracting information is hard!

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Myth3 : Computer is intelligent

Pros• Repeated work• Accurate storage• Precise computation• Fast communication…

Cons• Cannot generalize• No real intelligence…

The results must be reviewed and validated by biologists. In addition, biologists must have some understanding of how computer processes data (algorithms) – that’s why we need to learn bioinformatics.

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Biology – Bioinformatics

Bioinformatics

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High-throughput techniques

DNA Sequencing

• 1970’s – Nobel prize• 1980’s – Ph.D. thesis• Early 1990’s – Major

research projects• Late 1990’s to now - $20

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Human Genome ProjectThe Beginning (1988)

Cold Spring Harbor LaboratoryLong Island, New York

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Initial Analysis of the Human Genome

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What information do we want to extract?

Science, 9/2/2005 Total genetic difference (# of bases) is 4%35 million single base substitutions plus 5 million insertions or deletions (indels)

The average protein differs by only two amino acids, and 29% of proteins are identical.

Genotype – Phenotype relationship!!!

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Phenotype• mRNA level

• Protein expression

• Protein structure

• Cell morphology

• Tissue morphology

• System physiological functions

• Behavior

• …

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High-throughput techniques

High throughput protein crystalization

Mass spectrometry

Microarray

High throughput cell imaging

High throughput in vivo screening

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How to extract the information?

Computational tools

• Building the databases

• Perform analysis/extract features

• Data funsion/Integration

• Data mining/Classification/statistical

learning

• Visualization/representation

Biological information!!!

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What we are going to do:

• Search the databases

• Perform analysis

• Present output

Be a salient user!

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What the scope of Bioinformatics teach?

• Genomics

• Proteomics

• Microarray analysis

• Other aspects

• Ontology

• Machine learning / statistical analysis

• Visualization

• Data sources (databases)

• Available tools

• Major issues in using the

databases and tools

• Other resources

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Review of Biology

Central dogma

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Review of Biology

Operon

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Review of Biology

mRNA, cDNA,

exon, intron

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Review of Biology

Protein folding and structure

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Databases

GenBank www.ncbi.nlm.nih.gov/GenBank/EMBL www.ebi.ac.uk/embl/DDBJ www.ddbj.nig.ac.jpSynchronized daily.Accession numbers are managed in a consistent way.

AceDBDDJP DNAJJPIDMIPSPHREDPIRPROSITERDPTIGRUNIGENE…

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Resources

Local: OSU library

Web: PubMedJSTOR (http://www.jstor.com)http://www.expasy.orghttp://www.genecards.orghttp://www.pathguide.org/

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PubMed – Entrez

PubMed : http://www.pubmed.gov, http://www.ncbi.nlm.nih.gov/entrez/query.fcgiPubMed training : http://www.nlm.nih.gov/bsd/disted/pubmed.htmlEntrez : http://www.ncbi.nlm.nih.gov/Database/index.html

Entrez is the integrated, text-based search and retrieval system used at NCBI for the major databases, including PubMed, Nucleotide and Protein Sequences, Protein Structures, Complete Genomes, Taxonomy, and others. Click on the graphic below for a more detailed view of Entrez integration.

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Entrez Databases

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LiteraturesExamples:

1. E2F32. Retinoblastoma

Constraints: automatics vs. manual

Save: Tutorial at http://www.nlm.nih.gov/bsd/viewlet/myncbi/saving_searches.swf

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Literatures

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Literatures

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LiteraturesExamples:

1. E2F32. Retinoblastoma

Constraints: automatics vs. manual

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Literatures

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Nucleotide• Gene• Genome• Sequence• mRNA• cDNA• SNP• ESTs (expressed sequence tags) / UniGene

• Name• Accession number• GI number• Version number• Alias

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Accession number, GI number, Version• accession number (GenBank) - The accession number is the unique identifier

assigned to the entire sequence record when the record is submitted to

GenBank. The GenBank accession number is a combination of letters and

numbers that are usually in the format of one letter followed by five digits (e.g.,

M12345) or two letters followed by six digits (e.g., AC123456). • The accession number for a particular record will not change even if the author submits a request to

change some of the information in the record. Take note that an accession number is a unique identifier for

a complete sequence record, while a Sequence Identifier, such as a Version, GI, or ProteinID, is an

identification number assigned just to the sequence data. The NCBI Entrez System is searchable by

accession number using the Accession [ACCN] search field.

• GI (GenBank) - A GI or "GenInfo Identifier" is a sequence identifier that can be

assigned to a nucleotide sequence or protein translation. Each GI is a numeric

value of one or more digits. The protein translation and the nucleotide sequence

contained in the same record will each be assigned different GI numbers. • Every time the sequence data for a particular record is changed, its version number increases and it

receives a new GI. However, while each new version number is based upon the previous version number, a

new GI for an altered sequence may be completely different from the previous GI. For example, in the

GenBank record M12345, the original GI might be 7654321, but after a change in the sequence is

submitted, the new GI for the changed sequence could be 10529376. Individuals can search for nucleotide

sequences and protein translations by GI using the UID search field in the NCBI sequence databases.

• GI number is NOT GeneID.

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Example : E2F3

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Example : E2F3

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Data FormatFASTA (.fasta file) >gi|33469954|ref|NM_000240.2| Homo sapiens monoamine oxidase A (MAOA), nuclear

gene encoding mitochondrial protein, mRNA GGGCGCTCCCGGAGTATCAGCAAAAGGGTTCGCCCCGCCCACAGTGCCCGGCTCCCCCCGGGTATCAAAA GAAGGATCGGCTCCGCCCCCGGGCTCCCCGGGGGAGTTGATAGAAGGGTCCTTCCCACCCTTTGCCGTCC CCACTCCTGTGCCTACGACCCAGGAGCGTGTCAGCCAAAGCATGGAGAATCAAGAGAAGGCGAGTATCGC GGGCCACATGTTCGACGTAGTCGTGATCGGAGGTGGCATTTCAGGACTATCTGCTGCCAAACTCTTGACT GAATATGGCGTTAGTGTTTTGGTTTTAGAAGCTCGGGACAGGGTTGGAGGAAGAACATATACTATAAGGA ATGAGCATGTTGATTACGTAGATGTTGGTGGAGCTTATGTGGGACCAACCCAAAACAGAATCTTACGCTT GTCTAAGGAGCTGGGCATAGAGACTTACAAAGTGAATGTCAGTGAGCGTCTCGTTCAATATGTCAAGGGG AAAACATATCCATTTCGGGGCGCCTTTCCACCAGTATGGAATCCCATTGCATATTTGGATTACAATAATC TGTGGAGGACAATAGATAACATGGGGAAGGAGATTCCAACTGATGCACCCTGGGAGGCTCAACATGCTGA CAAATGGGACAAAATGACCATGAAAGAGCTCATTGACAAAATCTGCTGGACAAAGACTGCTAGGCGGTTT GCTTATCTTTTTGTGAATATCAATGTGACCTCTGAGCCTCACGAAGTGTCTGCCCTGTGGTTCTTGTGGT ATGTGAAGCAGTGCGGGGGCACCACTCGGATATTCTCTGTCACCAATGGTGGCCAGGAACGGAAGTTTGT AGGTGGATCTGGTCAAGTGAGCGAACGGATAATGGACCTCCTCGGAGACCAAGTGAAGCTGAACCATCCT GTCACTCACGTTGACCAGTCAAGTGACAACATCATCATAGAGACGCTGAACCATGAACATTATGAGTGCA AATACGTAATTAATGCGATCCCTCCGACCTTGACTGCCAAGATTCACTTCAGACCAGAGCTTCCAGCAGA GAGAAACCAGTTAATTCAGCGGCTTCCAATGGGAGCTGTCATTAAGTGCATGATGTATTACAAGGAGGCC TTCTGGAAGAAGAAGGATTACTGTGGCTGCATGATCATTGAAGATGAAGATGCTCCAATTTCAATAACCT TGGATGACACCAAGCCAGATGGGTCACTGCCTGCCATCATGGGCTTCATTCTTGCCCGGAAAGCTGATCG ACTTGCTAAGCTACATAAGGAAATAAGGAAGAAGAAAATCTGTGAGCTCTATGCCAAAGTGCTGGGATCC CAAGAAGCTTTACATCCAGTGCATTATGAAGAGAAGAACTGGTGTGAGGAGCAGTACTCTGGGGGCTGCT ACACGGCCTACTTCCCTCCTGGGATCATGACTCAATATGGAAGGGTGATTCGTCAACCCGTGGGCAGGAT TTTCTTTGCGGGCACAGAGACTGCCACAAAGTGGAGCGGCTACATGGAAGGGGCAGTTGAGGCTGGAGAA CGAGCAGCTAGGGAGGTCTTAAATGGTCTCGGGAAGGTGACCGAGAAAGATATCTGGGTACAAGAACCTG

>gi|4557735|ref|NP_000231.1| monoamine oxidase A [Homo sapiens] MENQEKASIAGHMFDVVVIGGGISGLSAAKLLTEYGVSVLVLEARDRVGGRTYTIRNEHVDYVDVGGAYV GPTQNRILRLSKELGIETYKVNVSERLVQYVKGKTYPFRGAFPPVWNPIAYLDYNNLWRTIDNMGKEIPT DAPWEAQHADKWDKMTMKELIDKICWTKTARRFAYLFVNINVTSEPHEVSALWFLWYVKQCGGTTRIFSV TNGGQERKFVGGSGQVSERIMDLLGDQVKLNHPVTHVDQSSDNIIIETLNHEHYECKYVINAIPPTLTAK IHFRPELPAERNQLIQRLPMGAVIKCMMYYKEAFWKKKDYCGCMIIEDEDAPISITLDDTKPDGSLPAIM GFILARKADRLAKLHKEIRKKKICELYAKVLGSQEALHPVHYEEKNWCEEQYSGGCYTAYFPPGIMTQYG RVIRQPVGRIFFAGTETATKWSGYMEGAVEAGERAAREVLNGLGKVTEKDIWVQEPESKDVPAVEITHTF WERNLPSVSGLLKIIGFSTSVTALGFVLYKYKLLPRS

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Data Format

Other formats

NBRF/PIR (.pir file)Begin with “>P1;” for protein sequence and “>N1;” for nucleotide.

GDE (.gde file) Similar to FASTA file, begin with “%” instead of “>”.

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Protein DatabasesUniProt is the universal protein database, a central repository of protein data created by combining Swiss-Prot, TrEMBL and PIR. This makes it the world's most comprehensive resource on protein information.The Protein Information Resource (PIR), located at Georgetown University Medical Center (GUMC), is an integrated public bioinformatics resource to support genomic and proteomic research, and scientific studies. Swiss-Prot is a curated biological database of protein sequences from different species created in 1986 by Amos Bairoch during his PhD and developed by the Swiss Institute of Bioinformatics and the European Bioinformatics Institute. Pfam is a large collection of multiple sequence alignments and hidden Markov models covering many common protein domains and families. PDBNCBIhttp://proteome.nih.gov/links.html

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PubMed – Protein DatabasesThe Protein database contains sequence data from the translated coding regions from DNA sequences in GenBank, EMBL, and DDBJ as well as protein sequences submitted to Protein Information Resource (PIR), SWISS-PROT, Protein Research Foundation (PRF), and Protein Data Bank (PDB) (sequences from solved structures).

The Structure database or Molecular Modeling Database (MMDB) contains experimental data from crystallographic and NMR structure determinations. The data for MMDB are obtained from the Protein Data Bank (PDB). The NCBI has cross-linked structural data to bibliographic information, to the sequence databases, and to the NCBI taxonomy. Use Cn3D, the NCBI 3D structure viewer, for easy interactive visualization of molecular structures from Entrez.

Tutorial: http://www.pdb.org/pdbstatic/tutorials/tutorial.html

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Example – UniProt - Expasyhttp://www.uniprot.org/ http://www.expasy.org/

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Example – UniProt - Expasy

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Example – UniProt - Expasy

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Example – UniProt - Expasy

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Example – UniProt - Expasy

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Annotation - Visualization

UCSC Genome Browser (http://genome.ucsc.edu/)