3.9 Article

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

期刊

SCIENTIFIC WORLD JOURNAL
卷 -, 期 -, 页码 -

出版社

HINDAWI LTD
DOI: 10.1155/2014/864135

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资金

  1. National Natural Science Foundation of China [61063016, 31160188]
  2. Scientific Research Program at Universities of Inner Mongolia Autonomous Region of China [NJZY13014]
  3. Natural Science Foundation of Inner Mongolia Autonomous Region of China [2013MS0504, 2013MS0503]
  4. Program of Higher-level Talents of Inner Mongolia University [135147]

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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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