Luis Francisco Hernández Sánchez1,2,3, Bram Burger4,5, Carlos Horro4,5, Antonio Fabregat3, Stefan Johansson1,2, Pål Rasmus Njølstad1,6, Harald Barsnes4,5, Henning Hermjakob3,7, Marc Vaudel1,2. 1. K.G. Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Children's Hospital, Haukeland University Hospital, 5021 Bergen, Norway. 2. Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, P.O Box 1400, 5021 Bergen, Norway. 3. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom. 4. Proteomics Unit, Department of Biomedicine, University of Bergen, Postbox 7804, 5020 Bergen, Norway. 5. Computational Biology Unit, Department of Informatics, University of Bergen, P.O. Box 7803, 5020 Bergen, Norway. 6. Department of Pediatrics, Haukeland University Hospital, 5021 Bergen, Norway. 7. Beijing Proteome Research Center, National Center for Protein Sciences Beijing, No. 38, Life Science Park Road, Changping District, 102206 Beijing, China.
Abstract
BACKGROUND: Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. FINDINGS: Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. CONCLUSIONS: PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein.
BACKGROUND: Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. FINDINGS: Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. CONCLUSIONS: PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein.
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