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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Detalles Bibliográficos
Autores principales: Zheng, Cheng, Wang, Mingjun, Takemoto, Kazuhiro, Akutsu, Tatsuya, Zhang, Ziding, Song, Jiangning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499040/
https://www.ncbi.nlm.nih.gov/pubmed/23166753
http://dx.doi.org/10.1371/journal.pone.0049716

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499040/
https://www.ncbi.nlm.nih.gov/pubmed/23166753
http://dx.doi.org/10.1371/journal.pone.0049716

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