Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach

@article{Lin2006PredictionOT,
  title={Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach},
  author={H. H. Lin and L. Y. Han and H. L. Zhang and C. J. Zheng and B. Xie and Zhi-Wei Cao and Yu Zong Chen},
  journal={BMC Bioinformatics},
  year={2006},
  volume={7},
  pages={S13 - S13}
}
Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins irrespective of sequence similarity. This work explores support vector machines (SVM) as such a method. SVM prediction systems were developed by using 53,333 metal-binding and 147,347 non-metal… CONTINUE READING
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