DocumentCode
1319438
Title
Enhanced Encoding with Improved Fuzzy Decision Tree Testing Using CASP Templates
Author
Chida, Anjum ; Zhang, Yan-Qing ; Harrison, Robert
Author_Institution
Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA
Volume
7
Issue
4
fYear
2012
Firstpage
55
Lastpage
60
Abstract
A novel protein model assessment technique using an improved fuzzy decision tree was tested using CASP8 and CASP9 templates. The testing was conducted in three phases. In the first two phases, templates were classified without explicit scoring. In phase three, a new scoring method was created for performance evaluation. The new protein model assessment technique was compared with several common prominent model assessment techniques for CASP competitions. The performance was analyzed based on correlation between our scores and GDT_TS scores of the templates. Finally, it is concluded that although the novel protein model assessment technique resulted in reduced correlation when compared to best competitors in CASP, its uniqueness in using the improved fuzzy decision tree and a single model stands as a new paradigm in the protein model assessment field.
Keywords
biology computing; decision trees; encoding; fuzzy set theory; pattern classification; proteins; CASP8 templates; CASP9 templates; GDT-TS scores; critical assessment of structure prediction; encoding enhancement; fuzzy decision tree testing; global distance test-total score; protein model assessment technique; scoring method; template classification; Bioinformatics; Biological system modeling; Decision trees; Genomics; Informatics; Proteins;
fLanguage
English
Journal_Title
Computational Intelligence Magazine, IEEE
Publisher
ieee
ISSN
1556-603X
Type
jour
DOI
10.1109/MCI.2012.2215134
Filename
6331721
Link To Document