Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids
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- 作者：Gaurav Raicara ; raicar_g@usp.ac.fj" class="auth_mail" title="E-mail the corresponding author ; Harsh Sainia ; saini_h@usp.ac.fj" class="auth_mail" title="E-mail the corresponding author ; Abdollah Dehzangib ; i.dehzangi@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Sunil Lalc ; s.lal@massey.ac.nz" class="auth_mail" title="E-mail the corresponding author ; Alok Sharmaa ; d ; e ; sharma_al@usp.ac.fj" class="auth_mail" title="E-mail the corresponding author
- 关键词：Protein fold recognition ; Structural class prediction ; Physicochemical properties ; Syntactical-based features ; Evolutionary-based features ; Forward consecutive search scheme
- 刊名：Journal of Theoretical Biology
- 出版年：2016
- 出版时间：7 August 2016
- 年：2016
- 卷：402
- 期：Complete
- 页码：117-128
- 全文大小：1460 K
文摘
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A Forward Consecutive Search (FCS) scheme is proposed.
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Physicochemical attributes are strategically selected.
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Physicochemical-based features supplement existing feature extraction techniques.
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Improvements in prediction accuracies after utilizing physicochemical information.