An SVM-Based Algorithm for Classifying Promoter-Associated CpG Islands in the Human and Mouse Genomes

• Published in: Advanced Intelligent Computing Theories and Applications Vol. 5227; pp. 975 - 981
• Main Authors: Han, Leng, Yang, Ruolin, Su, Bing, Zhao, Zhongming
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2008; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: CpG islands (CGIs); human; mouse; promoter; Support Vector Machine (SVM)
• ISBN: 9783540859833; 3540859837
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-85984-0_117

CpG islands (CGIs) are clusters of CpG dinucleotides in GC-rich regions and represent an important gene feature of mammalian genomes. Several algorithms have been developed to identify CGIs. Here we applied Support Vector Machine (SVM), a machine learning approach, to classify CGIs that are associated with the promoter regions of genes. We demonstrated that our SVM-based algorithm had much higher sensitivity and specificity in classifying promoter-associated CGIs than other algorithms, and had high reliability. The advantages of SVM in our method and future improvements were discussed.