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Exercise 1Exercise 1Bioinformatics DatabasesBioinformatics Databases

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What’s in a databaseWhat’s in a database?? Sequences – genes, proteins, etc.Sequences – genes, proteins, etc.

Full genomesFull genomes

Annotation – information about the gene/protein:Annotation – information about the gene/protein:- function- function- cellular location- cellular location- chromosomal location- chromosomal location- introns/exons- introns/exons- protein structure- protein structure- phenotypes, diseases- phenotypes, diseases

PublicationsPublications

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NCBI and EntrezNCBI and Entrez

One of the largest and most comprehensive One of the largest and most comprehensive databases belonging to the NIH – national databases belonging to the NIH – national institute of health (USA)institute of health (USA)

Entrez is the search engine of NCBIEntrez is the search engine of NCBI Search for :Search for :

genes, proteins, genomes, structures, diseases, genes, proteins, genomes, structures, diseases, publications and morepublications and more..

httphttp://://wwwwww..ncbincbi..nlmnlm..nihnih..govgov//

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Searching for published papersSearching for published papers Yang X, Kurteva S, Ren X, Lee S,Yang X, Kurteva S, Ren X, Lee S,

Sodroski JSodroski J.. “Subunit stoichiometry of human “Subunit stoichiometry of human immunodeficiency virus type 1 envelope glycoprotein trimers immunodeficiency virus type 1 envelope glycoprotein trimers during virus entry into host cells “, J Virolduring virus entry into host cells “, J Virol.. 2006 2006 May;80(9):4388-95. May;80(9):4388-95.

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Use fieldsUse fields!!Yang[AU] AND glycoprotein[TI] AND 2006[DP] AND J virol[TA]

For the full list of field tags: go to help -> Search Field Descriptions and Tags

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ExerciseExercise

Retrieve all publications in which the Retrieve all publications in which the first first author is:author is: Pe'er I Pe'er I and the and the last author is:last author is: Shamir RShamir R

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Using LimitsUsing Limits

Retrieve the publications of Friedman N, in the journals: Bioinformatics and Journal of Computational Biology, in the last 5 years

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Google scholarGoogle scholarhttp://scholar.google.com/

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NCBI gene & protein databases: NCBI gene & protein databases: GenBankGenBank

GenBankGenBank is an annotated collection of all is an annotated collection of all publicly available DNA sequencespublicly available DNA sequences

Holds Holds 65 billion65 billion bases (Oct. 2007)bases (Oct. 2007)

GenPeptGenPept is a database of translated is a database of translated coding sequences from GenBankcoding sequences from GenBank

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Searching for CD4 human using Searching for CD4 human using EntrezEntrez

Search demonstrationSearch demonstration

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Using Field Descriptions, Qualifiers, Using Field Descriptions, Qualifiers, and Boolean Operatorsand Boolean Operators

Cd4[GENE] AND human[ORGN] Cd4[GENE] AND human[ORGN] Or Or Cd4[gene name] AND human[organism]Cd4[gene name] AND human[organism]

List of field codes: List of field codes: httphttp://://wwwwww..ncbincbi..nlmnlm..nihnih..govgov//entrezentrez//queryquery//staticstatic//helphelp//Summary_MatricesSummary_Matrices..html#Search_Fields_and_Qualifiershtml#Search_Fields_and_Qualifiers

Boolean Operators:Boolean Operators:ANDANDORORNOTNOT

Note: do not use the field Protein name [PROT], only Note: do not use the field Protein name [PROT], only GENE!GENE!

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RefSeqRefSeq REFSEQ: sub-collection of NCBI databases with REFSEQ: sub-collection of NCBI databases with

only non-redundant, highly annotated entries only non-redundant, highly annotated entries (genomic DNA, transcript (RNA), and protein (genomic DNA, transcript (RNA), and protein products)products)

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1717An explanation on GenBank records

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Accession NumbersAccession NumbersGenBankGenBank

EMBLEMBL

Two letters followed by six digits, e.g.:Two letters followed by six digits, e.g.:AY123456AY123456

One letter followed by five digits, eOne letter followed by five digits, e..gg.:.:U12345U12345

GenPept (a.a. GenPept (a.a. translations of translations of GenBank)GenBank)

Three letters and five digits, e.g.:Three letters and five digits, e.g.:AAA12345AAA12345

RefseqRefseqRefSeq accession numbers can be distinguished from RefSeq accession numbers can be distinguished from GenBank accessions by their prefix distinct format of GenBank accessions by their prefix distinct format of [[2 2 characters+underscorecharacters+underscore]], e.g.: , e.g.: NP_015325NP_015325..NM_: nucleotide, NP_: proteinNM_: nucleotide, NP_: protein

SWISSSWISS--PROTPROT

(another protein (another protein database)database)

All are six charactersAll are six characters::Character/FormatCharacter/Format1 [O,P,Q] 2 [0-9] 3 [A-Z,0-9] 4 [A-Z,0-9]1 [O,P,Q] 2 [0-9] 3 [A-Z,0-9] 4 [A-Z,0-9]5 [A-Z,0-9] 6 [0-9] 5 [A-Z,0-9] 6 [0-9] e.g.:e.g.:P12345P12345 and and Q9JJS7Q9JJS7

PDB (Protein Data PDB (Protein Data Bank – structure Bank – structure database)database)

one digit followed by three letters, eone digit followed by three letters, e..gg.:.:1hxw1hxw

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Swiss-ProtSwiss-Prot

A protein sequence database which A protein sequence database which strives to provide a high level of strives to provide a high level of annotation:annotation:* the function of a protein* the function of a protein* domains structure* domains structure* post* post--translational modificationstranslational modifications* variants* variants

One entry for each proteinOne entry for each protein

2020

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GenBank Vs. Swiss-ProtGenBank Vs. Swiss-Prot

GenBank results Swiss-Prot results

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Downloading a sequence & Fasta formatDownloading a sequence & Fasta format

Fasta formatFasta format

> gi|10835167|ref|NP_000607.1| CD4 antigen precursor [Homo sapiens] MNRGVPFRHLLLVLQLALLPAATQGKKVVLGKKGDTVELTCTASQKKSIQFHWKNSNQIKILGNQGSFLTKGPSKLNDRADSRRSLWDQGNFPLIIKNLKIEDSDTYICEVEDQKEEVQLLVFGLTANSDTHLLQGQSLTLTLESPPGSSPSVQCRSPRGKNIQGGKTLSVSQLELQDSGTWTCTVLQNQKKVEFKIDIVVLAFQKASSIVYKKEGEQVEFSFPLAFTVEKLTGSGELWWQAERASSSKSWITFDLKNKEVSVKRVTQDPKLQMGKKLPLHLTLPQALPQYAGSGNLTLALEAKTGKLHQEVNLVVMRATQLQKNLTCEVWGPTSPKLMLSLKLENKEAKVSKREKAVWVLNPEAGMWQCLLSDSGQVLLESNIKVLPTWSTPVQPMALIVLGGVAGLLLFIGLGIFFCVRCRHRRRQAERMSQIKRLLSEKKTCQCPHRFQKTCSPI

Save Accession Numbers for future use (makes searching quicker):Refseq: NP_000607.1Swiss-Prot: P01730

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PDBPDB:: Protein Data Bank Protein Data Bank

Main database of 3D structuresMain database of 3D structures Includes ~47,000 entries (Includes ~47,000 entries (proteinsproteins, ,

nucleic acids, others)nucleic acids, others) Proteins organized in groups, families etc.Proteins organized in groups, families etc. Is highly redundantIs highly redundant http://www.rcsb.orghttp://www.rcsb.org

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CD4 in complex with gp120CD4 in complex with gp120

gp120

CD4

PDB ID 1G9M

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Model organisms have independent database:Model organisms have independent database:

Organism specific databasesOrganism specific databases

HIV database http://hiv-web.lanl.gov/content/index

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GenecardsGenecards

All in one database of human genes (a All in one database of human genes (a project by Weizmann institute) project by Weizmann institute)

Attempts to integrate as many as possible Attempts to integrate as many as possible databases, publications and all available databases, publications and all available knowledgeknowledge

httphttp://://wwwwww..genecardsgenecards..orgorg

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SummarySummary

General and comprehensive databases:General and comprehensive databases: NCBI, EMBL, DDBJNCBI, EMBL, DDBJ

Genome specific databases:Genome specific databases: ENSEMBL, UCSC genome browserENSEMBL, UCSC genome browser

Highly annotated databases:Highly annotated databases: Human genesHuman genes

• Genecards Genecards Proteins:Proteins:

• Swiss-Prot, RefseqSwiss-Prot, Refseq Structures:Structures:

• PDBPDB

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The MOST important of allThe MOST important of all

1.1.GoogleGoogle (or any search engine) (or any search engine)

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And always rememberAnd always remember::

2.2.RT(F)MRT(F)M – –

Read the manual!!Read the manual!!

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HelpHelp!!

Read the Help sectionRead the Help section Read the FAQ sectionRead the FAQ section Google the question!Google the question!

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|| || ||||| ||| || || |||||||||||||||||||MVHLTPEEKTAVNALWGKVNVDAVGGEALGRLLVVYPWTQRFFE…

ATGGTGAACCTGACCTCTGACGAGAAGACTGCCGTCCTTGCCCTGTGGAACAAGGTGGACGTGGAAGACTGTGGTGGTGAGGCCCTGGGCAGGTTTGTATGGAGGTTACAAGGCTGCTTAAGGAGGGAGGATGGAAGCTGGGCATGTGGAGACAGACCACCTCCTGGATTTATGACAGGAACTGATTGCTGTCTCCTGTGCTGCTTTCACCCCTCAGGCTGCTGGTCGTGTATCCCTGGACCCAGAGGTTCTTTGAAAGCTTTGGGGACTTGTCCACTCCTGCTGCTGTGTTCGCAAATGCTAAGGTAAAAGCCCATGGCAAGAAGGTGCTAACTTCCTTTGGTGAAGGTATGAATCACCTGGACAACCTCAAGGGCACCTTTGCTAAACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGATCCTGAGAATTTCAAGGTGAGTCAATATTCTTCTTCTTCCTTCTTTCTATGGTCAAGCTCATGTCATGGGAAAAGGACATAAGAGTCAGTTTCCAGTTCTCAATAGAAAAAAAAATTCTGTTTGCATCACTGTGGACTCCTTGGGACCATTCATTTCTTTCACCTGCTTTGCTTATAGTTATTGTTTCCTCTTTTTCCTTTTTCTCTTCTTCTTCATAAGTTTTTCTCTCTGTATTTTTTTAACACAATCTTTTAATTTTGTGCCTTTAAATTATTTTTAAGCTTTCTTCTTTTAATTACTACTCGTTTCCTTTCATTTCTATACTTTCTATCTAATCTTCTCCTTTCAAGAGAAGGAGTGGTTCACTACTACTTTGCTTGGGTGTAAAGAATAACAGCAATAGCTTAAATTCTGGCATAATGTGAATAGGGAGGACAATTTCTCATATAAGTTGAGGCTGATATTGGAGGATTTGCATTAGTAGTAGAGGTTACATCCAGTTACCGTCTTGCTCATAATTTGTGGGCACAACACAGGGCATATCTTGGAACAAGGCTAGAATATTCTGAATGCAAACTGGGGACCTGTGTTAACTATGTTCATGCCTGTTGTCTCTTCCTCTTCAGCTCCTGGGCAATATGCTGGTGGTTGTGCTGGCTCGCCACTTTGGCAAGGAATTCGACTGGCACATGCACGCTTGTTTTCAGAAGGTGGTGGCTGGTGTGGCTAATGCCCTGGCTCACAAGTACCATTGA

MVNLTSDEKTAVLALWNKVDVEDCGGEALGRLLVVYPWTQRFFE…

Alignment teaserAlignment teaser……

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Pairwise Pairwise Sequence Sequence AlignmentAlignment

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What is sequence alignmentWhat is sequence alignment??

Alignment: Alignment: Comparing two (pairwise) or Comparing two (pairwise) or more (multiple) sequences. Searching for more (multiple) sequences. Searching for a series of identical or similar characters in a series of identical or similar characters in the sequences.the sequences.

MVNLTSDEKTAVLALWNKVDVEDCGGE|| || ||||| ||| || || ||MVHLTPEEKTAVNALWGKVNVDAVGGE

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Why sequence alignment?Why sequence alignment?

Predict characteristics of a protein – Predict characteristics of a protein –

use the structure or function information on use the structure or function information on known proteins with similar sequences available known proteins with similar sequences available in databases in order to predict the structure or in databases in order to predict the structure or function of an unknown proteinfunction of an unknown protein

Assumptions: similar sequences Assumptions: similar sequences produce similar proteinsproduce similar proteins

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Local vs. GlobalLocal vs. Global Global alignmentGlobal alignment – finds the best – finds the best

alignment across the alignment across the wholewhole two two sequences.sequences.

Local alignmentLocal alignment – finds regions of – finds regions of high similarity in high similarity in partsparts of the of the sequences.sequences.

ADLGAVFALCDRYFQ|||| |||| |ADLGRTQN-CDRYYQ

ADLG CDRYFQ|||| |||| |ADLG CDRYYQ

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In the course of evolution, the sequences changed In the course of evolution, the sequences changed from the ancestral sequence by random mutationsfrom the ancestral sequence by random mutations

Three types of changes:Three types of changes:1.1. InsertionInsertion - AAGA - AAGA AAG AAGTTAA

Sequence evolutionSequence evolution

AAGAAGAA

InsertionInsertion

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In the course of evolution, the sequences changed In the course of evolution, the sequences changed from the ancestral sequence by random mutationsfrom the ancestral sequence by random mutations

Three types of Three types of changeschanges : :1.1. InsertionInsertion - AAGA - AAGA AAG AAGTTAA

2.2. DeletionDeletion - - AAAAGAGA AGA AGA

Sequence evolutionSequence evolution

AA AGAG

DeletionDeletion

AA

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In the course of evolution, the sequences In the course of evolution, the sequences changed from the ancestral sequence by changed from the ancestral sequence by random mutationsrandom mutations

Three types of mutations:Three types of mutations:

1.1. InsertionInsertion - AAGA - AAGA AAG AAGTTAA

2.2. DeletionDeletion - A - AAAGAGA AGA AGA

3.3. SubstitutionSubstitution -- AA AAGGAA AA AACCAA

Evolutionary changes in sequencesEvolutionary changes in sequences

AAAA AA

SubstitutionSubstitution

GGCC

InsertionInsertion + + DeletionDeletion IndelIndel

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Sequence alignmentSequence alignment

AAGCTGAATTCGAAAGGCTCATTTCTGA

AAGCTGAATT-C-GAAAGGCT-CATTTCTGA-

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Scoring schemeScoring scheme

Match/mismatch scores: substitution matricesMatch/mismatch scores: substitution matrices Nucleic acids:Nucleic acids:

• Transition-transversionTransition-transversion Amino acids:Amino acids:

• Evolution (empirical data) based: (PAM, BLOSUM)Evolution (empirical data) based: (PAM, BLOSUM)• Physico-chemical properties based (Grantham, Physico-chemical properties based (Grantham,

McLachlan)McLachlan)

Gap penaltyGap penalty

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Amino Acid Scoring MatricesAmino Acid Scoring Matrices PAM matrices: PAM80, PAM120, PAM250PAM matrices: PAM80, PAM120, PAM250

The number with PAM matrices represent The number with PAM matrices represent evolutionary distance evolutionary distance

Greater numbers denote greater distancesGreater numbers denote greater distances Low PAM: strong similaritiesLow PAM: strong similarities High PAM: weak similaritiesHigh PAM: weak similarities

PAM120 for general use (40% identity)PAM120 for general use (40% identity) PAM60 for close relations (60% identity)PAM60 for close relations (60% identity) PAM250 for distant relations (20% identity)PAM250 for distant relations (20% identity)

If uncertain, try several different If uncertain, try several different matricesmatrices

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Amino Acid Scoring MatricesAmino Acid Scoring Matrices BLOSUM matrices: BLOSUM45, BLOSUM62, BLOSUM matrices: BLOSUM45, BLOSUM62,

BLOSUM80BLOSUM80 The number with BLOSUM matrices represent The number with BLOSUM matrices represent

average % identity average % identity Greater numbers denote greater identityGreater numbers denote greater identity Low BLOSUM: weak similaritiesLow BLOSUM: weak similarities High BLOSUM: strong similaritiesHigh BLOSUM: strong similarities

BLOSUM62 for general use BLOSUM62 for general use BLOSUM80 for close relations BLOSUM80 for close relations BLOSUM45 for distant relationsBLOSUM45 for distant relations

If uncertain, try several different matricesIf uncertain, try several different matrices

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Web servers for pairwise alignmentWeb servers for pairwise alignment

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BLAST 2 sequences (bl2Seq) at BLAST 2 sequences (bl2Seq) at NCBI NCBI

Produces the Produces the locallocal alignment of two given alignment of two given sequences using sequences using BLASTBLAST (Basic Local (Basic Local Alignment Search Tool)Alignment Search Tool) engine for local engine for local alignmentalignment

Does not use an optimal algorithm but a Does not use an optimal algorithm but a heuristicheuristic

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Back to NCBIBack to NCBI

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BLAST – bl2seqBLAST – bl2seq

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blastnblastn – nucleotide – nucleotide

blastpblastp – protein – protein

Bl2Seq - queryBl2Seq - query

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Bl2seq resultsBl2seq results

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Bl2seq resultsBl2seq results

MatchMatch DissimilarityDissimilarity GapsGaps SimilaritySimilarity Low Low

complexitycomplexity

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Bl2seq resultsBl2seq results::

Bits scoreBits score – A score for the alignment according – A score for the alignment according to the number of identities, similarities, etc.to the number of identities, similarities, etc.

Expected-score (E-value)Expected-score (E-value) –The number of –The number of alignments with the same score one can alignments with the same score one can “expect” to observe by chance when searching a “expect” to observe by chance when searching a database of a particular size. The closer the e-database of a particular size. The closer the e-value approaches zero, the greater the value approaches zero, the greater the confidence that the hit is realconfidence that the hit is real

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BLAST – programsBLAST – programs

Query: DNA Protein

Database: DNA Protein

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BLAST – BlastpBLAST – Blastp

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Blastp - resultsBlastp - results

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Blastp – results (cont’)Blastp – results (cont’)

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Blastp – acquiring sequencesBlastp – acquiring sequences

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Blastp – acquiring sequences Blastp – acquiring sequences (cont’)(cont’)

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Fasta format – multiple sequencesFasta format – multiple sequences>gi|4504351|ref|NP_000510.1| delta globin [Homo sapiens] MVHLTPEEKTAVNALWGKVNVDAVGGEALGRLLVVYPWTQRFFESFGDLSSPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFSQLSELHCDKLHVDPENFRLLGNVLVCVLARNFGKEFTPQMQAAYQKVVAGVAN ALAHKYH

>gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

>gi|4885393|ref|NP_005321.1| epsilon globin [Homo sapiens] MVHFTAEEKAAVTSLWSKMNVEEAGGEALGRLLVVYPWTQRFFDSFGNLSSPSAILGNPKVKAHGKKVLT SFGDAIKNMDNLKPAFAKLSELHCDKLHVDPENFKLLGNVMVIILATHFGKEFTPEVQAAWQKLVSAVAI ALAHKYH

>gi|6715607|ref|NP_000175.1| G-gamma globin [Homo sapiens] MGHFTEEDKATITSLWGKVNVEDAGGETLGRLLVVYPWTQRFFDSFGNLSSASAIMGNPKVKAHGKKVLT SLGDAIKHLDDLKGTFAQLSELHCDKLHVDPENFKLLGNVLVTVLAIHFGKEFTPEVQASWQKMVTGVAS ALSSRYH

>gi|28302131|ref|NP_000550.2| A-gamma globin [Homo sapiens] MGHFTEEDKATITSLWGKVNVEDAGGETLGRLLVVYPWTQRFFDSFGNLSSASAIMGNPKVKAHGKKVLT SLGDATKHLDDLKGTFAQLSELHCDKLHVDPENFKLLGNVLVTVLAIHFGKEFTPEVQASWQKMVTAVAS ALSSRYH

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Searching for remote homologsSearching for remote homologs

Sometimes BLAST isn’t enoughSometimes BLAST isn’t enough Large protein family, and BLAST only finds Large protein family, and BLAST only finds

close members. We want more distant close members. We want more distant members members

PSI-BLASTPSI-BLAST Profile HMMs (not discussed)Profile HMMs (not discussed)

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PSI-BLASTPSI-BLAST

PPosition osition SSpecific pecific IIterated BLASTterated BLAST

Regular blast

Construct profile from blast results

Blast profile search

Final results

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PSI-BLASTPSI-BLAST

Advantage:Advantage: PSI-BLAST looks for seq’s PSI-BLAST looks for seq’s that are close to the query, and learns that are close to the query, and learns from them to extend the circle of friendsfrom them to extend the circle of friends

Disadvantage:Disadvantage: if we obtained a WRONG if we obtained a WRONG hit, we will get to unrelated sequences hit, we will get to unrelated sequences (contamination). This gets worse and (contamination). This gets worse and worse each iterationworse each iteration

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BLAST – PSI-BlastBLAST – PSI-Blast

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PSI-Blast - resultsPSI-Blast - results