Briefing in Application of Machine Learning Methods in Ion Channel PredictionReport as inadecuate

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The Scientific World Journal - Volume 2015 2015, Article ID 945927, 7 pages -

Review Article

Key Laboratory for Neuro-Information of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China

Department of Physics, School of Sciences and Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China

Received 31 July 2014; Accepted 11 September 2014

Academic Editor: Ramu Anandakrishnan

Copyright © 2015 Hao Lin and Wei Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In cells, ion channels are one of the most important classes of membrane proteins which allow inorganic ions to move across the membrane. A wide range of biological processes are involved and regulated by the opening and closing of ion channels. Ion channels can be classified into numerous classes and different types of ion channels exhibit different functions. Thus, the correct identification of ion channels and their types using computational methods will provide in-depth insights into their function in various biological processes. In this review, we will briefly introduce and discuss the recent progress in ion channel prediction using machine learning methods.

Author: Hao Lin and Wei Chen



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