Prediction of Transmembrane Proteins from Their Primary Sequence by Support Vector Machine Approach.
C. Z. CaiQ. F. YuanH. G. XiaoX. H. LiuL. Y. HanYu Zong ChenPublished in: ICIC (3) (2006)
Keyphrases
- support vector machine
- amino acid residues
- amino acids
- amino acid sequences
- stock market prediction
- protein structure
- protein tertiary structure
- subcellular localization
- prediction accuracy
- sequence similarity
- contact map
- drug design
- multiple sequence alignments
- protein sequences
- prediction model
- sequence prediction
- multi class
- protein structure prediction
- protein function
- sequence analysis
- wet lab
- predicting protein
- protein interaction
- protein protein interactions
- contact maps
- svm classifier
- molecular biology
- protein secondary structure
- feature selection
- protein structural
- computational biology
- support vector
- tertiary structure
- multiple sequence alignment
- protein function prediction
- protein families
- data sets
- radial basis function
- support vector machine svm
- feature vectors
- training data
- neural network