Title
Exploring alternative knowledge representations for protein secondary-structure prediction.
Abstract
Methods for 3-class secondary-structure prediction are thought to be reaching the highest achievable accuracy. Their accuracy on beta-sheet residue class is considerably lower than for the other two classes. We analysed the relevance of 315 individual input attributes for a predictor with the usual framework of using sequence-profile based data with an input window of fixed size. We propose two alternative knowledge representations with significantly smaller sets of input attributes. We also investigated the possibility of exploiting the prediction of connected pairs of beta-sheet residues and the prediction of residue contact maps for the improvement of accuracy of secondary-structure prediction.
Year
DOI
Venue
2007
10.1504/IJDMB.2007.011614
IJDMB
Keywords
DocType
Volume
3-class secondary-structure prediction,alternative knowledge representation,sheet residue,accuracy ofsecondary-structure prediction,input attribute,sheet residue class,input window,highest achievable accuracy,prediction ofconnected pair,prediction ofresidue contact map,protein secondary-structure prediction
Journal
1
Issue
ISSN
Citations 
3
1748-5673
2
PageRank 
References 
Authors
0.41
6
3
Name
Order
Citations
PageRank
Uros Midic191.61
A. Keith Dunker246677.54
Zoran Obradovic31110137.41