Enhancing protein-vitamin binding residues prediction by multiple heterogeneous subspace SVMs ensemble.
Dong-Jun YuJun HuHui YanXibei YangJing-Yu YangHong-Bin ShenPublished in: BMC Bioinform. (2014)
Keyphrases
- contact map
- protein sequences
- protein structure
- protein structure prediction
- amino acids
- protein tertiary structure
- contact maps
- protein chains
- support vector
- training set
- subcellular localization
- feature selection
- protein folding
- ensemble methods
- prediction accuracy
- protein function
- majority voting
- amino acid sequences
- experimentally determined
- principal component analysis
- mhc class ii
- protein structure alignment
- amino acid composition
- multiple sequence alignments
- predicting protein
- drug design
- support vector machine
- feature space
- tertiary structure
- multiple sequence alignment
- ensemble classifier
- neural networks and support vector machines
- generalization ability
- random forest
- support vector machine svm
- dimensionality reduction
- training data