Splice Site Prediction Using Support Vector Machines with a Bayes Kernel

• Main Authors: ZHANG, Ya, CHU, Chao-Hsien, CHEN, Yixin, ZHA, Hongyuan, JI, Xiang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: Splice site prediction; SVM; Support vector machines; Bayes classifier; Machine learning; Splice Site Prediction Using Support Vector Machines with Bayes Kernel; Computer Sciences; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1163; http://dx.doi.org/10.1016/j.eswa.2005.09.052
• Institution: Singapore Management University

One of the most important tasks in correctly annotating genes in higher organisms is to accurately locate the DNA splice sites. Although relatively high accuracy has been achieved by existing methods, most of these prediction methods are computationally extensive. Due to the enormous amount of DNA s...