Evidence map›Paper›PMID 21767381›Full record

ArticleBMC bioinformatics2011

Bio::Homology::InterologWalk--a Perl module to build putative protein-protein interaction networks through interolog mapping.

Giuseppe Gallone, T Ian Simpson, J Douglas Armstrong, Andrew P Jarman

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In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Giuseppe GalloneCentre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK. G.Gallone@sms.ed.ac.uk
T Ian Simpson
J Douglas Armstrong
Andrew P Jarman

Funding

Biotechnology and Biological Sciences Research Council BB/I004491/1Medical Research Council G68293XWellcome Trust 077266
6 · The paper itself

Abstract

backgroundProtein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or 'interologs'. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for 'on-the-fly' interolog prediction.

resultsWe introduce Bio::Homology::InterologWalk, a Perl module to retrieve, prioritise and visualise putative protein-protein interactions through an orthology-walk method. The module uses orthology and experimental interaction data to generate putative PPIs and optionally collates meta-data into an Interaction Prioritisation Index that can be used to help prioritise interologs for further analysis. We show the application of our interolog prediction method to the genomic interactome of the fruit fly, Drosophila melanogaster. We analyse the resulting interaction networks and show that the method proposes new interactome members and interactions that are candidates for future experimental investigation.

conclusionsOur interolog prediction tool employs the Ensembl Perl API and PSICQUIC enabled protein interaction data sources to generate up to date interologs 'on-the-fly'. This represents a significant advance on previous methods for interolog prediction as it allows the use of the latest orthology and protein interaction data for all of the genomes in Ensembl. The module outputs simple text files, making it easy to customise the results by post-processing, allowing the putative PPI datasets to be easily integrated into existing analysis workflows. The Bio::Homology::InterologWalk module, sample scripts and full documentation are freely available from the Comprehensive Perl Archive Network (CPAN) under the GNU Public license.

Indexed as

Protein Interaction MappingSoftwareAnimalsDrosophila melanogasterDrosophila ProteinsGenome, InsectProteomicsDrosophila Proteins

Identifiers

PMID21767381
PMCPMC3161927

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.