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Operon prediction based on SVM

Paper ID Volume ID Publish Year Pages File Format Full-Text
15469 1415 2006 8 PDF Available
Title
Operon prediction based on SVM
Abstract

The operon is a specific functional organization of genes found in bacterial genomes. Most genes within operons share common features. The support vector machine (SVM) approach is here used to predict operons at the genomic level. Four features were chosen as SVM input vectors: the intergenic distances, the number of common pathways, the number of conserved gene pairs and the mutual information of phylogenetic profiles. The analysis reveals that these common properties are indeed characteristic of the genes within operons and are different from that of non-operonic genes. Jackknife testing indicates that these input feature vectors, employed with RBF kernel SVM, achieve high accuracy. To validate the method, Escherichia coli K12 and Bacillus subtilis were taken as benchmark genomes of known operon structure, and the prediction results in both show that the SVM can detect operon genes in target genomes efficiently and offers a satisfactory balance between sensitivity and specificity.

Keywords
Operon; SVM; Feature
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Operon prediction based on SVM
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 30, Issue 3, June 2006, Pages 233–240
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us