HomoMINT: An inferred human network based on orthodology mapping of protein interactions discovered in model organisms

Maria Persico, Arnaud Ceol, Caius Gavrila, Robert Hoffman, Arnaldo Florio, Gianni Cesareni

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The application of high throughput approaches to the identification of protein interactions has offered for the first time a glimpse of the global interactome of some model organisms. Until now, however, such genome-wide approaches have not been applied to the human proteome. Results: In order to fill this gap we have assembled an inferred human protein interaction network where interactions discovered in model organisms are mapped onto the corresponding human orthologs. In addition to a stringent assignment to orthology classes based on the In Paranoid algorithm, we have implemented a string matching algorithm to filter out orthology assignments of proteins whose global domain organization is not conserved. Finally, we have assessed the accuracy of our own, and related, inferred networks by benchmarking them against i) an assembled experimental interactome, ii) a network derived by mining of the scientific literature and iii) by measuring the enrichment of interacting protein pairs sharing common Gene Ontology annotation. Conclusion: The resulting networks are named HomoMINT and HomoMINT_filtered, the latter being based on the orthology table filtered by the domain architecture matching algorithm. They contains 9749 and 5203 interactions respectively and can be analyzed and viewed in the context of the experimentally verified interactions between human proteins stored in the MINT database. HomoMINT is constantly updated to take into account the growing information in the MINT database.

Original languageEnglish
Article numberS21
JournalBMC Bioinformatics
Volume6
Issue numberSUPPL.4
DOIs
Publication statusPublished - Dec 1 2005

ASJC Scopus subject areas

  • Medicine(all)
  • Structural Biology
  • Applied Mathematics

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