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Re: protein identification problem

From: Gary Bader <bader@cbio.mskcc.org>
Date: Thu, 30 Jun 2005 21:59:09 -0400
Message-ID: <42C4A36D.7000201@cbio.mskcc.org>
To: public-semweb-lifesci@w3.org

Hi,
	I agree with Ken that gene name to database ID resolution is a major 
issue in bioinformatics.  I'd also like to add that database ID to 
database ID resolution (alias resolution) is a major issue as well.  I 
think these issues represent a fantastic opportunity to showcase 
semantic web technologies and drive their use in bioinformatics and I 
would argue that if these issues can't be resolved, then the semantic 
web will not function well for biologists.  We just need someone out 
there to implement them.
	To be more specific about use cases, here is an extract of a document I 
wrote in the context of a pathway database, but the use cases are much 
more general.  (And in fact, as David States mentioned at the BOF, more 
links than these simple ones can be contemplated e.g. sequence 
similarity links)

-----

Links between database identifiers are required for four specific 
use-cases in a typical pathway database. Most of the database 
identifiers are for molecules (proteins, small molecules), but 
identifiers for complexes, interactions, pathways, molecular states, 
etc. are also required, but are less important in the short to mid term 
(e.g. next 1-2 years).

Use cases:
1.	Unification during dataset merging: During a merge operation e.g. of 
two protein-protein interaction datasets from independently created 
databases, it is vital to recognize that two protein objects, one from 
each data source, represent the same protein molecule, even if the 
protein objects don’t share any database accession numbers. Unification 
requires knowledge of record type e.g. you cannot reliably use a gene ID 
to unify proteins (mostly because splice variants exist).
2.	Link out to related references: When presenting information about a 
protein to a user on a web page, it is useful to display links to 
related information about the protein, such as further information about 
the protein sequence and sequence feature annotations (e.g. in 
SwissProt), Gene Ontology annotations, domains annotations (InterPro), etc.
3.	Identifier translation: Some analysis methods require specific 
translations from one set of identifiers to another.  For instance, the 
‘activity centers’ analysis requires translation from protein or gene 
identifiers in a pathway database to Affymetrix probe set identifiers or 
other gene expression array platform identifiers.
4.	Searching for a favorite gene name: Preferred gene names used for 
querying a pathway database should return all genes/proteins with that 
name, if they exist in the database. Unlike database accession numbers, 
gene names are not guaranteed unique, thus cannot reliably be used for 
the other use cases.

Links are available from many sources, but not every source addresses 
each use case (and none address all use cases).  All services that allow 
all data to be downloaded can conceivably be used for all use cases with 
the help of a separate software system that can store different link 
types (e.g. unification links, link out links), although this also 
requires recognition of record type (e.g. protein, small molecule, 
reaction, etc.).

Mapping services

AliasServer
http://cbi.labri.fr/outils/alias/
Tool for identifier translation using CRC64 hash of the protein sequence 
as a primary key. Provides unification, linkout and translation services 
for a handful (~35) species for proteins only.  Supports use cases 2, 3.

Freely available for download. Regularly updated.

MD Anderson GeneLink
http://bioinformatics.mdanderson.org/GeneLink.html
ID translation and search service for human IDs (10 ID types).  Supports 
use case 2, 3.

EnsMart
http://www.ensembl.org/Multi/martview
ID translation services for Ensembl genomes. Supports use case 2.

MatchMiner
http://discover.nci.nih.gov/matchminer/html/index.jsp
ID translation service for mouse and human. Supports use cases 2, 3.

Ariadne Genomics ID Mapping Service
http://www.ariadnegenomics.com/services/idmap.html
Tool for identifier translation. Supports 7 species and maps between 12 
different ID types mainly for proteins and genes.
Commercial service, not available for download
Supports use case 3

GeneLynx
http://www.genelynx.org/
Provides linkout services for human, mouse and rat.  Supports use case 2.

NetAffx
http://www.affymetrix.com/products/software/specific/netaffx.affx
Provides ID translation services for Affy probe set IDs.  Supports use 
case 3.

http://openbns.sourceforge.net/ - Supports use cases 2,3

Databases

International Protein Index
http://www.ebi.ac.uk/IPI/IPIhelp.html
A cross reference database for proteins in higher eukaryotic organisms 
(5 species). Provides protein and gene cross references. Supports use 
case 1.

Entrez Gene
Provides detailed information on genes from multiple organisms including 
gene aliases and links to NCBI related resources. Supports use case 4 
(and 2 to some degree).

UniProt (SwissProt, PIR, TrEMBL) provides some information on links to 
related resources and protein names.




Ken I Fukuda wrote:
> Hi all,
> 
> In the ISMB Semantic web for Life Science BOF,
> an issue was raised about the ambiguity of how people
> refer to a protein in the literature.
> 
> For example, let's say, you find a description such as
> "JNK activates JUN" but acctually this "JNK" stands for
> a bunch of proteins ("concrete entities") and JUN
> also stands for a set of proteins.
> 
> This isssue is known as the "generic entitity" problem.
> If you read the literature, you typically encounter these
> "generic protein" names.
> And there should be a mechanism that tells you how many
> proteins you have for each generic name.
> 
> An ontology for generic/concrete protein names, called
> "MoleculeRole Ontology" is available from
> http://www.inoh.org/ontology-viewer/.
> Actually, it is a DAG structured controled vocabulary (CV).
> The current version covers about 4400 Uniprot IDs which means
> that the CV defines generic/concrete protein relations for
> more than 4400 concrete proteins.
> 
> The CV is available in OBO format (Gene Ontology native format).
> http://www.inoh.org/download.html
> 
> PS.
> There are some OBO->OWL converters, but some argued they didn't
> fit their needs. It would be nice to know how people like to
> convert an OBO ontology into an OWL file.
> 
> Best,
> Ken
> 
> --------------------------------------------- 
> Ken Ichiro Fukuda, Ph.D.
> Computational Biology Research Center (CBRC)
> National Institute of 
> Advanced Industrial Science and Technology (AIST)
> AIST Tokyo Waterfront Bio-IT Research Bldg. 10F
> 2-42 Aomi, Koutou-ku, Tokyo 135-0064 JAPAN
> Phone: +81-3-3599-8049  FAX: +81-3-3599-8081
> fukuda-cbrc@aist.go.jp / fukuda_cbrc@yahoo.co.jp
>      - http://www.cbrc.jp/~fukuda/index.html
> - INOH Pathway Database Project -
>      - Integrating Network Objects with Hierarchies
>      - http://www.inoh.org
> 
> 
> 
> 
Received on Friday, 1 July 2005 01:58:49 GMT

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