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Briefing in Application of Machine Learning Methods in Ion Channel Prediction
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 a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415473/ https://www.ncbi.nlm.nih.gov/pubmed/25961077 http://dx.doi.org/10.1155/2015/945927 |
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author | Lin, Hao Chen, Wei |
author_facet | Lin, Hao Chen, Wei |
author_sort | Lin, Hao |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4415473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-44154732015-05-10 Briefing in Application of Machine Learning Methods in Ion Channel Prediction Lin, Hao Chen, Wei ScientificWorldJournal Review Article 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. Hindawi Publishing Corporation 2015 2015-04-16 /pmc/articles/PMC4415473/ /pubmed/25961077 http://dx.doi.org/10.1155/2015/945927 Text en Copyright © 2015 H. Lin and W. Chen. https://creativecommons.org/licenses/by/3.0/ 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. |
spellingShingle | Review Article Lin, Hao Chen, Wei Briefing in Application of Machine Learning Methods in Ion Channel Prediction |
title | Briefing in Application of Machine Learning Methods in Ion Channel Prediction |
title_full | Briefing in Application of Machine Learning Methods in Ion Channel Prediction |
title_fullStr | Briefing in Application of Machine Learning Methods in Ion Channel Prediction |
title_full_unstemmed | Briefing in Application of Machine Learning Methods in Ion Channel Prediction |
title_short | Briefing in Application of Machine Learning Methods in Ion Channel Prediction |
title_sort | briefing in application of machine learning methods in ion channel prediction |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4415473/ https://www.ncbi.nlm.nih.gov/pubmed/25961077 http://dx.doi.org/10.1155/2015/945927 |
work_keys_str_mv | AT linhao briefinginapplicationofmachinelearningmethodsinionchannelprediction AT chenwei briefinginapplicationofmachinelearningmethodsinionchannelprediction |