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Database (Oxford). 2015 Dec 26;2015. pii: bav117. doi: 10.1093/database/bav117. Print 2015.

HitPredict version 4: comprehensive reliability scoring of physical protein-protein interactions from more than 100 species.

Author information

1
Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan.
2
Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.
3
Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan ashwini@hgc.jp.

Abstract

HitPredict is a consolidated resource of experimentally identified, physical protein-protein interactions with confidence scores to indicate their reliability. The study of genes and their inter-relationships using methods such as network and pathway analysis requires high quality protein-protein interaction information. Extracting reliable interactions from most of the existing databases is challenging because they either contain only a subset of the available interactions, or a mixture of physical, genetic and predicted interactions. Automated integration of interactions is further complicated by varying levels of accuracy of database content and lack of adherence to standard formats. To address these issues, the latest version of HitPredict provides a manually curated dataset of 398 696 physical associations between 70 808 proteins from 105 species. Manual confirmation was used to resolve all issues encountered during data integration. For improved reliability assessment, this version combines a new score derived from the experimental information of the interactions with the original score based on the features of the interacting proteins. The combined interaction score performs better than either of the individual scores in HitPredict as well as the reliability score of another similar database. HitPredict provides a web interface to search proteins and visualize their interactions, and the data can be downloaded for offline analysis. Data usability has been enhanced by mapping protein identifiers across multiple reference databases. Thus, the latest version of HitPredict provides a significantly larger, more reliable and usable dataset of protein-protein interactions from several species for the study of gene groups. Database URL: http://hintdb.hgc.jp/htp.

PMID:
26708988
PMCID:
PMC4691340
DOI:
10.1093/database/bav117
[Indexed for MEDLINE]
Free PMC Article

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