A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

Abstract
Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

Citation
A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction 2015:1 IEEE/ACM Transactions on Computational Biology and Bioinformatics

Publisher
Institute of Electrical and Electronics Engineers (IEEE)

Journal
IEEE/ACM Transactions on Computational Biology and Bioinformatics

DOI
10.1109/TCBB.2015.2505286

Additional Links
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7346422

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