| Literature DB >> 15993842 |
Kai-Yan Feng1, Yu-Dong Cai, Kuo-Chen Chou.
Abstract
A novel classifier, the so-called "LogitBoost" classifier, was introduced to predict the structural class of a protein domain according to its amino acid sequence. LogitBoost is featured by introducing a log-likelihood loss function to reduce the sensitivity to noise and outliers, as well as by performing classification via combining many weak classifiers together to build up a very strong and robust classifier. It was demonstrated thru jackknife cross-validation tests that LogitBoost outperformed other classifiers including "support vector machine," a very powerful classifier widely used in biological literatures. It is anticipated that LogitBoost can also become a useful vehicle in classifying other attributes of proteins according to their sequences, such as subcellular localization and enzyme family class, among many others.Mesh:
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Year: 2005 PMID: 15993842 DOI: 10.1016/j.bbrc.2005.06.075
Source DB: PubMed Journal: Biochem Biophys Res Commun ISSN: 0006-291X Impact factor: 3.575