{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:05:37Z","timestamp":1761843937415},"reference-count":36,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Bioinform. Comput. Biol."],"published-print":{"date-parts":[[2010,2]]},"abstract":"<jats:p> Alpha-helical transmembrane proteins mediate many key biological processes and represent 20%\u201330% of all genes in many organisms. Due to the difficulties in experimentally determining their high-resolution 3D structure, computational methods to predict the location and orientation of transmembrane helix segments using sequence information are essential. We present TOPTMH, a new transmembrane helix topology prediction method that combines support vector machines, hidden Markov models, and a widely used rule-based scheme. The contribution of this work is the development of a prediction approach that first uses a binary SVM classifier to predict the helix residues and then it employs a pair of HMM models that incorporate the SVM predictions and hydropathy-based features to identify the entire transmembrane helix segments by capturing the structural characteristics of these proteins. TOPTMH outperforms state-of-the-art prediction methods and achieves the best performance on an independent static benchmark. <\/jats:p>","DOI":"10.1142\/s0219720010004501","type":"journal-article","created":{"date-parts":[[2010,2,22]],"date-time":"2010-02-22T06:18:45Z","timestamp":1266819525000},"page":"39-57","source":"Crossref","is-referenced-by-count":5,"title":["TOPTMH: TOPOLOGY PREDICTOR FOR TRANSMEMBRANE \u03b1-HELICES"],"prefix":"10.1142","volume":"08","author":[{"given":"REZWAN","family":"AHMED","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA"}]},{"given":"HUZEFA","family":"RANGWALA","sequence":"additional","affiliation":[{"name":"Department of Computer Science, George Mason University, Fairfax, Virginia 22030, USA"}]},{"given":"GEORGE","family":"KARYPIS","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","first-page":"21","volume":"1","author":"Chen C. 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