An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes

Leng Han; Ruolin Yang; Bing Su; Zhongming Zhao

doi:10.1007/978-3-540-85984-0_117

An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes

Leng Han, Ruolin Yang, Bing Su, Zhongming Zhao

Bioinformatics & Computational Biology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English (US)
Title of host publication	Advanced Intelligent Computing Theories and Applications
Subtitle of host publication	With Aspects of Artificial Intelligence - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings
Pages	975-981
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-540-85984-0_117
State	Published - 2008
Event	4th International Conference on Intelligent Computing, ICIC 2008 - Shanghai, China Duration: Sep 15 2008 → Sep 18 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5227 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Conference on Intelligent Computing, ICIC 2008
Country/Territory	China
City	Shanghai
Period	9/15/08 → 9/18/08

Keywords

CpG islands (CGIs)
Human
Mouse
Promoter
Support Vector Machine (SVM)

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-85984-0_117

Cite this

Han, L., Yang, R., Su, B., & Zhao, Z. (2008). An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes. In Advanced Intelligent Computing Theories and Applications: With Aspects of Artificial Intelligence - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings (pp. 975-981). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5227 LNAI). https://doi.org/10.1007/978-3-540-85984-0_117

An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes. / Han, Leng; Yang, Ruolin; Su, Bing et al.
Advanced Intelligent Computing Theories and Applications: With Aspects of Artificial Intelligence - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings. 2008. p. 975-981 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5227 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Han, L, Yang, R, Su, B & Zhao, Z 2008, An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes. in Advanced Intelligent Computing Theories and Applications: With Aspects of Artificial Intelligence - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5227 LNAI, pp. 975-981, 4th International Conference on Intelligent Computing, ICIC 2008, Shanghai, China, 9/15/08. https://doi.org/10.1007/978-3-540-85984-0_117

Han L, Yang R, Su B, Zhao Z. An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes. In Advanced Intelligent Computing Theories and Applications: With Aspects of Artificial Intelligence - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings. 2008. p. 975-981. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-85984-0_117

Han, Leng ; Yang, Ruolin ; Su, Bing et al. / An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes. Advanced Intelligent Computing Theories and Applications: With Aspects of Artificial Intelligence - 4th International Conference on Intelligent Computing, ICIC 2008, Proceedings. 2008. pp. 975-981 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - 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.

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An SVM-Based algorithm for classifying promoter-associated CpG islands in the human and mouse genomes

Abstract

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Keywords

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