An Integrative Computational Framework Based on a Two-Step Random Forest Algorithm Improves Prediction of Zinc-Binding Sites in Proteins

Zinc-binding proteins are the most abundant metalloproteins in the Protein Data Bank where the zinc ions usually have catalytic, regulatory or structural roles critical for the function of the protein. Accurate prediction of zinc-binding sites is not only useful for the inference of protein function...

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Veröffentlicht in:PloS one Jg. 7; H. 11; S. e49716
Hauptverfasser: Zheng, Cheng, Wang, Mingjun, Takemoto, Kazuhiro, Akutsu, Tatsuya, Zhang, Ziding, Song, Jiangning
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Public Library of Science 14.11.2012
Public Library of Science (PLoS)
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ISSN:1932-6203, 1932-6203
Online-Zugang:Volltext
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