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. 2012 Jul;40(Web Server issue):W484-90.
doi: 10.1093/nar/gks458. Epub 2012 Jun 7.

IMP: A Multi-Species Functional Genomics Portal for Integration, Visualization and Prediction of Protein Functions and Networks

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Free PMC article

IMP: A Multi-Species Functional Genomics Portal for Integration, Visualization and Prediction of Protein Functions and Networks

Aaron K Wong et al. Nucleic Acids Res. .
Free PMC article

Abstract

Integrative multi-species prediction (IMP) 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 a framework for biologists to analyze their candidate gene sets in the context of functional networks, as they expand or focus these sets by mining functional relationships predicted from integrated high-throughput data. IMP integrates prior knowledge and data collections from multiple organisms in its analyses. Through flexible and interactive visualizations, researchers can compare functional contexts and interpret the behavior of their gene sets across organisms. Additionally, IMP identifies homologs with conserved functional roles for knowledge transfer, allowing for accurate function predictions even for biological processes that have very few experimental annotations in a given organism. IMP currently supports seven organisms (Homo sapiens, Mus musculus, Rattus novegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans and Saccharomyces cerevisiae), does not require any registration or installation and is freely available for use at http://imp.princeton.edu.

Figures

Figure 1.
Figure 1.
The workflow for creating and analyzing a custom gene set in IMP. (A) The interface for creating a gene set, where users can select an organism, add their genes and assign a label and informative color. This can be reached by following the ‘My Gene Sets’ link at the top right of every page. (B) The returned sub-network for the submitted gene set (large nodes), with the nodes colored using the user-assigned color for the custom set (red). Edge colors correspond to the confidence of a functional relationship between genes. Users can hover over any edge to examine the top data sets contributing to that score. (C) The added genes in the displayed network are functionally related to the queried genes at a confidence cutoff controlled by the user. (D) A biological process enrichment calculation is updated in real time as genes are added or removed from the network display. The user can choose to include annotations transferred from other organisms in the enrichment calculation.
Figure 2.
Figure 2.
The cross-organism network view in IMP. The functional networks for the double-strand break repair pathway are visually aligned, and any interactions in the queried network (human) are simultaneously updated in the other networks (mouse and yeast). Yellow nodes indicate genes that are annotated to the double-strand break repair pathway in the respective organism. Gray nodes are genes with a homolog in the query organism.
Figure 3.
Figure 3.
The result pages for a gene and biological process query. (A) A gene query returns the relevant local network and a list of biological processes predicted for the gene. The predicted processes can be searched by name or filtered by specificity (process size). (B) A biological process query returns a list of predicted genes likely to participate in the process. Clicking on a gene description will update the network on the left with relationships between the selected gene (large red node) and genes already known to be involved in the process (yellow nodes).

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