Abstract
IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu.
Keywords
BiologyCaenorhabditis elegansContext (archaeology)Model organismCompendiumComputational biologyFunctional genomicsDrosophila melanogasterGenomicsFunction (biology)GenomeGeneticsGene
MeSH Terms
AnimalsComputer GraphicsDiseaseGene Regulatory NetworksGenesGenomicsHumansInternetMiceProtein Interaction MappingProteinsRatsSoftwareSystems Integration
Affiliated Institutions
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Publication Info
- Year
- 2015
- Type
- article
- Volume
- 43
- Issue
- W1
- Pages
- W128-W133
- Citations
- 63
- Access
- Closed
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Cite This
Aaron K. Wong,
Arjun Krishnan,
Vicky Yao
et al.
(2015).
IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.
Nucleic Acids Research
, 43
(W1)
, W128-W133.
https://doi.org/10.1093/nar/gkv486
Identifiers
- DOI
- 10.1093/nar/gkv486
- PMID
- 25969450
- PMCID
- PMC4489318