Using GO-PseAA predictor to identify membrane proteins and their types
- 18 February 2005
- journal article
- Published by Elsevier in Biochemical and Biophysical Research Communications
- Vol. 327 (3) , 845-847
- https://doi.org/10.1016/j.bbrc.2004.12.069
Abstract
No abstract availableKeywords
This publication has 22 references indexed in Scilit:
- SLLE for predicting membrane protein typesJournal of Theoretical Biology, 2005
- Predicting enzyme family class in a hybridization spaceProtein Science, 2004
- Weighted-support vector machines for predicting membrane protein types based on pseudo-amino acid compositionProtein Engineering, Design and Selection, 2004
- Application of SVM to predict membrane protein typesJournal of Theoretical Biology, 2004
- Support Vector Machines for Predicting Membrane Protein Types by Using Functional Domain CompositionBiophysical Journal, 2003
- Prediction of Protein Structural Classes and Subcellular LocationsCurrent Protein & Peptide Science, 2000
- Prediction of Membrane Protein Types Based on the Hydrophobic Index of Amino AcidsProtein Journal, 2000
- Prediction of membrane protein types and subcellular locationsProteins-Structure Function and Bioinformatics, 1999
- The SWISS-PROT protein sequence data bank and its supplement TrEMBLNucleic Acids Research, 1997
- Prediction of Protein Structural ClassesCritical Reviews in Biochemistry and Molecular Biology, 1995