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acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition
Joint Authors
Fan, Guo-Liang
Liu, Yan-Ling
Zuo, Yong-Chun
Mei, Han-Xue
Rang, Yi
Hou, Bao-Yan
Zhao, Yan
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-02
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Fan, Guo-Liang& Liu, Yan-Ling& Zuo, Yong-Chun& Mei, Han-Xue& Rang, Yi& Hou, Bao-Yan…[et al.]. 2014. acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1051398
Modern Language Association (MLA)
Fan, Guo-Liang…[et al.]. acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1051398
American Medical Association (AMA)
Fan, Guo-Liang& Liu, Yan-Ling& Zuo, Yong-Chun& Mei, Han-Xue& Rang, Yi& Hou, Bao-Yan…[et al.]. acACS: Improving the Prediction Accuracy of Protein Subcellular Locations and Protein Classification by Incorporating the Average Chemical Shifts Composition. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1051398
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051398