Learning Models for Aligning Protein Sequences with Predicted Secondary Structure.
Eagu KimTravis J. WheelerJohn D. KececiogluPublished in: RECOMB (2009)
Keyphrases
- learning models
- protein sequences
- secondary structure
- solvent accessibility
- computational biology
- experimentally determined
- amino acids
- protein structure
- predicting protein
- machine learning
- learning algorithm
- conditional random fields
- loss function
- protein function
- amino acid sequences
- learning tasks
- protein structure prediction
- protein classification
- multiple sequence alignment
- semi supervised learning
- protein secondary structure
- machine learning algorithms
- protein folding
- learning problems
- biological sequences
- multiple alignment
- structural motifs
- sequence analysis
- computational methods
- classification models
- sequence alignment
- rna sequences
- supervised learning
- information extraction
- tertiary structure
- neural network
- bayesian networks
- pairwise