Youngwoong Han, Choong-Hyun Sun, Min-Sung Kim, G. Yi
{"title":"Combined Database System for Binary Protein Interaction and Co-complex Association","authors":"Youngwoong Han, Choong-Hyun Sun, Min-Sung Kim, G. Yi","doi":"10.1109/IACSIT-SC.2009.42","DOIUrl":null,"url":null,"abstract":"Protein-protein interaction (PPI) data has been tremendously increased by enhancement in proteomic technologies. Both binary protein interactions and protein complexes have been recognized as valuable sources for protein functional study. Great portion of the binary protein interactions are, however, predicted or inferred ones by computational methods from protein complex data. Validity of these data remains yet in unacceptable status. Hence, it is necessary to combine binary protein interactions and protein complex data for the sake of comprehensiveness while making clear distinction between them in well classified organization. We constructed a web-based database system that combines binary protein interaction and protein complex data from the nine most reliable public databases. Especially, the system maintains validity of data by adequately categorizing PPIs into direct binary interaction, co-complex relationship, and predicted interaction. In addition, we implemented a comprehensive user interface by which they can access relevant information at maximum. For single or group of queried proteins and their homologs, the system reports binary interactions, complexes, protein conservation in complexes, and binary interactions in complexes with their respective evidences. Our system would be a useful resource for identification of functionally correlated candidates in more reliable and comprehensive way. The system is currently available at http://piech.icu.ac.kr/ppi","PeriodicalId":286158,"journal":{"name":"2009 International Association of Computer Science and Information Technology - Spring Conference","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Association of Computer Science and Information Technology - Spring Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IACSIT-SC.2009.42","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Protein-protein interaction (PPI) data has been tremendously increased by enhancement in proteomic technologies. Both binary protein interactions and protein complexes have been recognized as valuable sources for protein functional study. Great portion of the binary protein interactions are, however, predicted or inferred ones by computational methods from protein complex data. Validity of these data remains yet in unacceptable status. Hence, it is necessary to combine binary protein interactions and protein complex data for the sake of comprehensiveness while making clear distinction between them in well classified organization. We constructed a web-based database system that combines binary protein interaction and protein complex data from the nine most reliable public databases. Especially, the system maintains validity of data by adequately categorizing PPIs into direct binary interaction, co-complex relationship, and predicted interaction. In addition, we implemented a comprehensive user interface by which they can access relevant information at maximum. For single or group of queried proteins and their homologs, the system reports binary interactions, complexes, protein conservation in complexes, and binary interactions in complexes with their respective evidences. Our system would be a useful resource for identification of functionally correlated candidates in more reliable and comprehensive way. The system is currently available at http://piech.icu.ac.kr/ppi