A strategy to select suitable physicochemical attributes of amino acids for protein fold recognition

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• 作者：Alok Sharma (5) (5)
  Kuldip K Paliwal (4)
  Abdollah Dehzangi (4)
  James Lyons (4)
  Seiya Imoto (5)
  Satoru Miyano (5)
  
• 刊名：BMC Bioinformatics
• 出版年：2013
• 出版时间：December 2013
• 年：2013
• 卷：14
• 期：1
• 全文大小：314KB
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• 作者单位：Alok Sharma (5) (5)
  Kuldip K Paliwal (4)
  Abdollah Dehzangi (4)
  James Lyons (4)
  Seiya Imoto (5)
  Satoru Miyano (5)
  
  5. School of Engineering and Physics, University of the South Pacific, Suva, Fiji
  4. School of Engineering, Griffith University, Brisbane, Australia
  
• ISSN：1471-2105

文摘

Background Assigning a protein into one of its folds is a transitional step for discovering three dimensional protein structure, which is a challenging task in bimolecular (biological) science. The present research focuses on: 1) the development of classifiers, and 2) the development of feature extraction techniques based on syntactic and/or physicochemical properties. Results Apart from the above two main categories of research, we have shown that the selection of physicochemical attributes of the amino acids is an important step in protein fold recognition and has not been explored adequately. We have presented a multi-dimensional successive feature selection (MD-SFS) approach to systematically select attributes. The proposed method is applied on protein sequence data and an improvement of around 24% in fold recognition has been noted when selecting attributes appropriately. Conclusion The MD-SFS has been applied successfully in selecting physicochemical attributes of the amino acids. The selected attributes show improved protein fold recognition performance.