Samuele Bovo1, Pietro Di Lena2, Pier Luigi Martelli1, Piero Fariselli3, Rita Casadio1,4. 1. Biocomputing Group, CIG, Interdepartmental Center «Luigi Galvani» for Integrated Studies of Bioinformatics, Biophysics and Biocomplexity, University of Bologna, Bologna, Italy. 2. DISI, University of Bologna, Bologna, Italy. 3. BCA, University of Padova, Padova, Italy. 4. Interdepartmental Center «Giorgio Prodi» for Cancer Research, University of Bologna, Bologna, Italy.
Abstract
MOTIVATION: Gene enrichment is a requisite for the interpretation of biological complexity related to specific molecular pathways and biological processes. Furthermore, when interpreting NGS data and human variations, including those related to pathologies, gene enrichment allows the inclusion of other genes that in the human interactome space may also play important key roles in the emergency of the phenotype. Here, we describe NET-GE, a web server for associating biological processes and pathways to sets of human proteins involved in the same phenotype RESULTS: NET-GE is based on protein-protein interaction networks, following the notion that for a set of proteins, the context of their specific interactions can better define their function and the processes they can be related to in the biological complexity of the cell. Our method is suited to extract statistically validated enriched terms from Gene Ontology, KEGG and REACTOME annotation databases. Furthermore, NET-GE is effective even when the number of input proteins is small. AVAILABILITY AND IMPLEMENTATION: NET-GE web server is publicly available and accessible at http://net-ge.biocomp.unibo.it/enrich CONTACT: gigi@biocomp.unibo.itSupplementary information: Supplementary data are available at Bioinformatics online.
MOTIVATION: Gene enrichment is a requisite for the interpretation of biological complexity related to specific molecular pathways and biological processes. Furthermore, when interpreting NGS data and human variations, including those related to pathologies, gene enrichment allows the inclusion of other genes that in the human interactome space may also play important key roles in the emergency of the phenotype. Here, we describe NET-GE, a web server for associating biological processes and pathways to sets of human proteins involved in the same phenotype RESULTS: NET-GE is based on protein-protein interaction networks, following the notion that for a set of proteins, the context of their specific interactions can better define their function and the processes they can be related to in the biological complexity of the cell. Our method is suited to extract statistically validated enriched terms from Gene Ontology, KEGG and REACTOME annotation databases. Furthermore, NET-GE is effective even when the number of input proteins is small. AVAILABILITY AND IMPLEMENTATION: NET-GE web server is publicly available and accessible at http://net-ge.biocomp.unibo.it/enrich CONTACT: gigi@biocomp.unibo.itSupplementary information: Supplementary data are available at Bioinformatics online.
Authors: Roman A Laskowski; James D Stephenson; Ian Sillitoe; Christine A Orengo; Janet M Thornton Journal: Protein Sci Date: 2019-10-27 Impact factor: 6.725