DocumentCode
3394139
Title
Comparison of feature selection techniques for viral DNA replication origin prediction
Author
Cruz-Cano, Raul ; Leung, Ming-Ying
Author_Institution
Texas A&M Univ.-Texarkana, Texarkana, TX
fYear
2009
fDate
March 30 2009-April 2 2009
Firstpage
128
Lastpage
134
Abstract
As the replication of their DNA genomes is a central step in the reproduction of many viruses, procedures to find replication origins, which are initiation sites of the DNA replication process, are of great importance for controlling the growth and spread of such viruses. Existing computational methods for viral replication origin prediction have mostly been designed to use only the composition of a region of viral DNA to predict if such region is an ORI or not. This paper proposes the application of several feature selection techniques to help find the most significant features of the replication origins in herpesviruses. The results suggest that features based on the relative positions of the regions in the genomes containing replication origins and the information about the subfamily of the virus can be highly useful features to be incorporated into the computational tools for viral replication origin prediction.
Keywords
DNA; biology computing; feature extraction; genomics; microorganisms; molecular biophysics; DNA genomes; feature selection technique; herpes virus; viral DNA replication origin prediction; Accuracy; Artificial neural networks; Bioinformatics; DNA; Genomics; Input variables; Machine learning; Sequences; Support vector machines; Viruses (medical);
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Bioinformatics and Computational Biology, 2009. CIBCB '09. IEEE Symposium on
Conference_Location
Nashville, TN
Print_ISBN
978-1-4244-2756-7
Type
conf
DOI
10.1109/CIBCB.2009.4925718
Filename
4925718
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