acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition

The chemical shift is sensitive to changes in the local environments and can report the structural changes. The structure information of a protein can be represented by the average chemical shifts (ACS) composition, which has been broadly applied for enhancing the prediction accuracy in protein subc...

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Autores principales: Fan, Guo-Liang, Liu, Yan-Ling, Zuo, Yong-Chun, Mei, Han-Xue, Rang, Yi, Hou, Bao-Yan, Zhao, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106170/
https://www.ncbi.nlm.nih.gov/pubmed/25110749
http://dx.doi.org/10.1155/2014/864135
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author Fan, Guo-Liang
Liu, Yan-Ling
Zuo, Yong-Chun
Mei, Han-Xue
Rang, Yi
Hou, Bao-Yan
Zhao, Yan
author_facet Fan, Guo-Liang
Liu, Yan-Ling
Zuo, Yong-Chun
Mei, Han-Xue
Rang, Yi
Hou, Bao-Yan
Zhao, Yan
author_sort Fan, Guo-Liang
collection PubMed
description The chemical shift is sensitive to changes in the local environments and can report the structural changes. The structure information of a protein can be represented by the average chemical shifts (ACS) composition, which has been broadly applied for enhancing the prediction accuracy in protein subcellular locations and protein classification. However, different kinds of ACS composition can solve different problems. We established an online web server named acACS, which can convert secondary structure into average chemical shift and then compose the vector for representing a protein by using the algorithm of auto covariance. Our solution is easy to use and can meet the needs of users.
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spelling pubmed-41061702014-08-10 acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition Fan, Guo-Liang Liu, Yan-Ling Zuo, Yong-Chun Mei, Han-Xue Rang, Yi Hou, Bao-Yan Zhao, Yan ScientificWorldJournal Research Article The chemical shift is sensitive to changes in the local environments and can report the structural changes. The structure information of a protein can be represented by the average chemical shifts (ACS) composition, which has been broadly applied for enhancing the prediction accuracy in protein subcellular locations and protein classification. However, different kinds of ACS composition can solve different problems. We established an online web server named acACS, which can convert secondary structure into average chemical shift and then compose the vector for representing a protein by using the algorithm of auto covariance. Our solution is easy to use and can meet the needs of users. Hindawi Publishing Corporation 2014 2014-07-02 /pmc/articles/PMC4106170/ /pubmed/25110749 http://dx.doi.org/10.1155/2014/864135 Text en Copyright © 2014 Guo-Liang Fan et al. 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 Research Article
Fan, Guo-Liang
Liu, Yan-Ling
Zuo, Yong-Chun
Mei, Han-Xue
Rang, Yi
Hou, Bao-Yan
Zhao, Yan
acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
title acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
title_full acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
title_fullStr acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
title_full_unstemmed acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
title_short acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
title_sort acacs: improving the prediction accuracy of protein subcellular locations and protein classification by incorporating the average chemical shifts composition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106170/
https://www.ncbi.nlm.nih.gov/pubmed/25110749
http://dx.doi.org/10.1155/2014/864135
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