temblor – perspectives of ebi database...

Conference Review

TEMBLOR – Perspectives of EBI databaseservicesA presentation for the ESF workshop ‘Data integration in functional genomicsand proteomics’

Henning Hermjakob* and Rolf ApweilerEuropean Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambrige CB10 1SD, UK

*Correspondence to:European Bioinformatics Institute,Wellcome Trust GenomeCampus, Hinxton, CambrigeCB10 1SD, UK.E-mail: [email protected]

Received: 21 November 2001

Accepted: 27 November 2001

Published online:

13 December 2001

Keywords: data integration; genomics; proteomics; protein–protein interaction

Rapid progress in sequencing during the last fewyears has led to the publication of the sequences ofaround 70 complete genomes. At least twice thatnumber is expected to be completed by the end of2002. The availability of complete genomic dataallows a whole range of new large-scale experimentssuch as the generation of whole-genome gene expres-sion data, high-throughput protein identificationby mass spectrometry, analysis of protein–proteininteractions by two-hybrid-systems, phage-display,tandem–affinity–purification or other methods.These and other types of high-throughput experi-ments all produce large quantities of data, whichmust be stored in robust databases to enable theiranalysis and exploitation. Much of this data iscurrently spread over many databases with differingstructures and locations making it difficult for usersto have an integrated view of the information. Tocope with data of such magnitude and complexity,higher interoperability of databases is essential.

Traditionally data distribution in the life sciencedomain takes the form of exchanges of ‘flat–files’,ie., ASCII text files in a database-specific format.Commercial and academic data providers and end-users retrieve these data sets, write tools to parse

them and reformat them usually in their ownformat to access them with their internal analysistools. Due to the dramatic increase of the quantityand complexity of biological data, it is clear thatdistribution and storage of data in flat-files willhave to be replaced in the future by more approp-riate systems. Various initiatives in the domain, e.g.SRS [4] or Entrez [3], are focused on access tointernal resources, by concentrating all the data inone central site and thus offering integrated views.The biggest drawback of such an approach is thatthese resources can only offer up-to-date data fordata collections maintained on site. Data fromexternal providers integrated in such a system willnever be up-to-date, and updating and maintaininglocal copies of external data collections in suchcentralised databases or data warehouses is a majortask.

Another approach is the federation of differentdatabases; each located at a different centre. Withall major molecular biology databases available onthe web, this has happened, on a very low level, bythe use of database cross-references providing linksfrom one database to one or many other relatedresources. This linking is initially easy to achieve,

Comparative and Functional Genomics

Comp Funct Genom 2002; 3: 47–50.DOI: 10.1002 / cfg.133

Copyright # 2001 John Wiley & Sons, Ltd.

will usually point users to the most recent data in across-referenced database, and makes maintenanceand updating of local copies of external databasesunnecessary. The drawback here is that thisapproach allows only linking on the coarse data-base entry level, and does not allow the computa-tion across databases or integrated views. However,this may be still the method of choice to integratesmall, specialised databases to core resources.

The InterPro [1] project, which provides anintegrated view of the protein domain and familysignature databases PROSITE, PRINTS, Pfam,SMART, TIGRFAM, and ProDom, as well as ofthe underlying protein sequence database SWISS-PROT + TrEMBL, uses a third way. InterPro triesto combine the advantages of a central databasewith the federated approach by creating a centralintegrative layer to store only the core data from itsmember databases and linking back to the richerdata at the individual member databases. Thisapproach allows minimising the hassle of updatingand maintaining local copies of external datacollections, while still allowing the computationacross databases or integrated views. The sameapproach of building an integrative layer to unifyresources while linking out to the original datasource for more detailed information will be used in

an initiative to create a next generation Europeanbioinformatics resource.

A consortium of 25 leading scientific organisa-tions from Europe and Israel, coordinated by theEuropean Bioinformatics Institute, has initiatedthe TEMBLOR project, which is funded by theEuropean Union and started in January 2002. TheTEMBLOR project will provide a highly integratedview of genomic and proteomic data (Integr8) bydrawing on databases maintained at major bio-informatics centres in Europe (Table 1). Newresources for patent, protein–protein interaction(IntAct), structural (EMSD), and microarray(DESPRAD) data will be created or will movefrom prototype to production status (Figure 1). TheIntegr8 component will enable text-, structure- andsequence-based searches against a gene-centric viewof all completed genomes. Zooming in on thesequence data linked to the gene will allow theuser to see genomic, transcriptional, and proteinsequences linked together. Each level will give directaccess to the whole body of scientific knowledgeabout a given gene, transcript or protein. Evidencetags will allow users to trace the original source ofdata and to quickly distinguish eg., betweenexperimentally verified and predicted data.

Building on the integrated database interface,

Table 1. Databases participating in the integration layer

Resource URL

ArrayExpress http://www.ebi.ac.uk/arrayexpress/

EMBL Nucleotide Sequence Database http://www.ebi.ac.uk/embl/index.html

CATH http://www.biochem.ucl.ac.uk/bsm/cath/

DbSNP http://www.ncbi.nlm.nih.gov/SNP/

EnsEMBL http://www.ensembl.org/

Eukaryotic Promoter Database (EPD) and EPDEX http://www.epd.isb-sib.ch/

Families of Structurally Similar Proteins (FSSP) http://www.ebi.ac.uk/dali/fssp/

Gene Ontology (GO) http://www.geneontology.org/

Homology derived Secondary Structure of Proteins (HSSP) http://www.sander.ebi.ac.uk/hssp/

HOBACGEN http://pbil.univ-lyon1.fr/databases/hobacgen.html

HOVERGEN http://pbil.univ-lyon1.fr/databases/hovergen.html

Human Genic Bi-Allelic Sequences Database (HGBASE) http://hgbase.cgr.ki.se/

InterPro (includes PROSITE, PRINTS, Pfam, ProDom and SMART) http://www.ebi.ac.uk/interpro/

Protein Data Bank (PDB) / European

Macromolecular Structure Database (EMSD)

http://msd.ebi.ac.uk/

Resource Center/Primary Database (RZPD) http://www.rzpd.de/

SWISS-2DPAGE http://www.expasy.org/ch/ch2d/

SWISS-MODEL Repository http://www.expasy.org/ch/swissmod/SM_3DCrunch_Search.html

SWISS-PROT + TrEMBL http://www.expasy.org/ch/sprot/

http://www.ebi.ac.uk/swissprot/

Transcription Factor Database (TRANSFAC) http://transfac.gbf.de/TRANSFAC/index.html

http://www.biobase.de

trEST and trGEN http://hits.isb-sib.ch/

48 H. Hermjakob and R. Apweiler

Copyright # 2001 John Wiley & Sons, Ltd. Comp Funct Genom 2002; 3: 47–50.

new tools tools and algorithms will allow the userto perform complex analysis of the data, includingwhole genome/proteome comparison and complexstrutural searches, eg., based on volume, surfaceand ligand chemistry. Queries will allow correlationof different data types, eg., expression data,protein–protein interaction data, and GO [5] anno-tation of the gene products involved. Applicationprogramming interfaces will be provided to allowcomplex third-party analysis of the data.

Specialised curators will maintain curatedgenome reviews and take up the ‘proteomicschallenge’ through extensive crosslinking and dataintegration: While genomic data is relatively wellaccessible due to the requirements for deposition inpublic repositories, proteomics data is often highlyfragmented across many species- or method-specificdatabases.

A central part of the TEMBLOR project areefforts for standardisation and international dataexchange. In the framework of the MicroarrayGene Expression Database Group (MGED) theMicroarray Gene Expression Markup Language

(MAGE-ML) and Microarray Gene ExpressionObject Model (MAGE-OM) standards for thedescription and exchange of microarray data willbe further refined, and the ArrayExpress databasewill be developed as a public database for micro-array data implementing these standards. TheMacromolecular Structure Database at the EBIwill further develop data exchange standards andtools for harvesting strutural data, and for dataexchange with the Protein Data Bank (PDB). TheIntAct project component will develop a standardfor the representation and exchange of protein–protein interaction data and establish a publicrepository for protein–protein interaction dataimplementing this standard. A portable version ofthe repository software will allow easy in-houseinstallation to facilitate the analysis of unpublishedand confidential data in the context of publiclyavailable data while at the same time allowing easysubmission to the public repository after publica-tion. In addition to third-party submissions, theIntAct protein–protein interaction database will bepopulated with experimental data from the project

Figure 1. Temblor project structure

TEMBLOR – Perspectives of EBI database services 49


partners, and with manually curated reference datasets. As a long-term goal, the IntAct project willstrive to establish an international data exchangefor protein–protein interaction data, similar to thenucleotide sequence data exchange between EMBL,GenBank and DDBJ, to overcome the current frag-mentation of publicly available protein–protein inter-action data. Successful cooperative projects likeGO, MGED, InterPro, or the EMBL/GenBank/DDBJ cooperation itself show the way to morecollaboration, data integration and data exchange,which ultimately provides better resources to theentire scientific community in bioinformatics andmolecular biology.

References

1. Apweiler R, Attwood TK, Bairoch A, et al. 2001. The

InterPro database, an integrated documentation resource for

protein families, domans and functional sites. Nucleic Acids

Res 29: 37–40.

2. Berman HM, Westbrook J, Feng Z, et al. 2000. The Protein

Data Bank. Nucleic Acids Res 28: 235–242.

3. Entrez. http://www.ncbi.nlm.nih.gov/Entrez/

4. Etzold T, Ulyanov A, Argos P. 1996. SRS: information

retrieval system for molecular biology data banks. Meth

Enzymol 266: 114–128.

5. The Gene Ontology Consortium. 2000. Gene Ontology: tool

for the unification of biology. Nat Genet 25: 25–29.

50 H. Hermjakob and R. Apweiler


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