{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T08:59:32Z","timestamp":1778057972878,"version":"3.51.4"},"reference-count":21,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2014K2A2A2000670"],"award-info":[{"award-number":["2014K2A2A2000670"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2015R1A1A3A04001243"],"award-info":[{"award-number":["2015R1A1A3A04001243"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2017,2]]},"abstract":"<jats:p> The interaction of virus proteins with host proteins plays a key role in viral infection and consequent pathogenesis. Many computational methods have been proposed to predict protein\u2013protein interactions (PPIs), but most of the computational methods are intended for PPIs within a species rather than PPIs across different species such as virus\u2013host PPIs. We developed a method that represents key features of virus and human proteins of variable length into a feature vector of fixed length. The key features include the relative frequency of amino acid triplets (RFAT), the frequency difference of amino acid triplets (FDAT) between virus and host proteins, and amino acid composition (AC). We constructed several support vector machine (SVM) models to evaluate our method and to compare our method with others on PPIs between human and two types of viruses: human papillomaviruses (HPV) and hepatitis C virus (HCV). Comparison of our method to others with same datasets of HPV\u2013human PPIs and HCV\u2013human PPIs showed that the performance of our method is significantly higher than others in all performance measures. Using the SVM model with gene ontology (GO) annotations of proteins, we predicted new HPV\u2013human PPIs. We believe our approach will be useful in predicting heterogeneous PPIs. <\/jats:p>","DOI":"10.1142\/s0219720016500244","type":"journal-article","created":{"date-parts":[[2016,7,11]],"date-time":"2016-07-11T02:25:49Z","timestamp":1468203949000},"page":"1650024","source":"Crossref","is-referenced-by-count":27,"title":["An improved method for predicting interactions between virus and human proteins"],"prefix":"10.1142","volume":"15","author":[{"given":"Byungmin","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Inha University, Incheon 22212, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saud","family":"Alguwaizani","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Inha University, Incheon 22212, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Inha University, Incheon 22212, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"De-Shuang","family":"Huang","sequence":"additional","affiliation":[{"name":"Machine Learning and Systems Biology Lab, College of Electronics and Information Engineering, Tongji University, Shanghai 201804, P. 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