Using LogitBoost classifier to predict protein structural classes
- 25 July 2005
- journal article
- Published by Elsevier in Journal of Theoretical Biology
- Vol. 238 (1) , 172-176
- https://doi.org/10.1016/j.jtbi.2005.05.034
Abstract
No abstract availableKeywords
This publication has 53 references indexed in Scilit:
- Using GO-PseAA predictor to identify membrane proteins and their typesBiochemical and Biophysical Research Communications, 2005
- SLLE for predicting membrane protein typesJournal of Theoretical Biology, 2005
- Using GO-PseAA predictor to predict enzyme sub-classBiochemical and Biophysical Research Communications, 2004
- Identify catalytic triads of serine hydrolases by support vector machinesJournal of Theoretical Biology, 2004
- Application of SVM to predict membrane protein typesJournal of Theoretical Biology, 2004
- A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontologyBiochemical and Biophysical Research Communications, 2003
- Prediction of protein cellular attributes using pseudo‐amino acid compositionProteins-Structure Function and Bioinformatics, 2001
- A Key Driving Force in Determination of Protein Structural ClassesBiochemical and Biophysical Research Communications, 1999
- A Decision-Theoretic Generalization of On-Line Learning and an Application to BoostingJournal of Computer and System Sciences, 1997
- A Joint Prediction of the Folding Types of 1490 Human Proteins from their Genetic CodonsJournal of Theoretical Biology, 1993