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...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2012-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3499040?pdf=render |