Using principal component analysis and support vector machine to predict protein structural class for low-similarity sequences via PSSM
Published 2012 View Full Article
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Title
Using principal component analysis and support vector machine to predict protein structural class for low-similarity sequences via PSSM
Authors
Keywords
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Journal
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
Volume 29, Issue 6, Pages 1138-1146
Publisher
Informa UK Limited
Online
2012-04-18
DOI
10.1080/07391102.2011.672627
References
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Note: Only part of the references are listed.- High-accuracy prediction of protein structural class for low-similarity sequences based on predicted secondary structure
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- (2009) Qiwen Dong et al. BIOINFORMATICS
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- Prediction of the protein structural class by specific peptide frequencies
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- SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
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- Prediction of protein structural class using novel evolutionary collocation-based sequence representation
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- Using support vector machines for prediction of protein structural classes based on discrete wavelet transform
- (2008) Jian-Ding Qiu et al. JOURNAL OF COMPUTATIONAL CHEMISTRY
- Predicting protein structural class by SVM with class-wise optimized features and decision probabilities
- (2008) Ashish Anand et al. JOURNAL OF THEORETICAL BIOLOGY
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- (2008) Hong-Bin Shen et al. JOURNAL OF THEORETICAL BIOLOGY
- PSLDoc: Protein subcellular localization prediction based on gapped-dipeptides and probabilistic latent semantic analysis
- (2008) Jia-Ming Chang et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- Exploring an alignment free approach for protein classification and structural class prediction
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- (2007) Tong-Liang Zhang et al. JOURNAL OF THEORETICAL BIOLOGY
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