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Although large amount of phosphorylation sites have been detected, unfortunately, it is rarely known which kinases activate those sites. Despite distinct computational approaches have been proposed to predict the kinase\u2013substrate interactions, the prediction accuracy still needs to be improved.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this paper, we propose a novel probabilistic model named as PhosD to predict kinase\u2013substrate relationships based on protein domains with the assumption that kinase\u2013substrate interactions are accomplished with kinase\u2013domain interactions. By further taking into account protein\u2013protein interactions, our PhosD outperforms other popular approaches on several benchmark datasets with higher precision. In addition, some of our predicted kinase\u2013substrate relationships are validated by signaling pathways, indicating the predictive power of our approach. Furthermore, we notice that given a kinase, the more substrates are known for the kinase the more accurate its predicted substrates will be, and the domains involved in kinase\u2013substrate interactions are found to be more conserved across proteins phosphorylated by multiple kinases. These findings can help develop more efficient computational approaches in the future.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and Implementation<\/jats:title><jats:p>The data and results are available at http:\/\/comp-sysbio.org\/phosd<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btw792","type":"journal-article","created":{"date-parts":[[2016,12,9]],"date-time":"2016-12-09T12:08:46Z","timestamp":1481285326000},"page":"1197-1204","source":"Crossref","is-referenced-by-count":18,"title":["PhosD: inferring kinase\u2013substrate interactions based on protein domains"],"prefix":"10.1093","volume":"33","author":[{"given":"Gui-Min","family":"Qin","sequence":"first","affiliation":[{"name":"School of Electronics and Information Engineering, Tongji University, Shanghai, China"},{"name":"School of Software, Xidian University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui-Yi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xing-Ming","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, Tongji University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,12,28]]},"reference":[{"key":"2023020205014109400_btw792-B1","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1038\/nbt1240","article-title":"A probability-based approach for high-throughput protein phosphorylation analysis and site localization","volume":"24","author":"Beausoleil","year":"2006","journal-title":"Nat. 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