A novel approach for classifying gene expression data using topic modeling

Soon Jye Kho; Michael L. Raymer; Hima Bindu Yalamanchili; Amit P. Sheth

doi:10.1145/3107411.3107483

A novel approach for classifying gene expression data using topic modeling

Soon Jye Kho, Michael L. Raymer, Hima Bindu Yalamanchili, Amit P. Sheth

Computer Science and Engineering

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

Original language	English
Title of host publication	ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
Publisher	Association for Computing Machinery, Inc
Pages	388-393
Number of pages	6
ISBN (Electronic)	9781450347228
DOIs	https://doi.org/10.1145/3107411.3107483
State	Published - Aug 20 2017
Event	8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2017 - Boston, United States Duration: Aug 20 2017 → Aug 23 2017

Publication series

Name	ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

Conference

Conference	8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2017
Country/Territory	United States
City	Boston
Period	8/20/17 → 8/23/17

ASJC Scopus Subject Areas

Software
Biomedical Engineering
Health Informatics
Computer Science Applications

Keywords

Cancer
Classification
Clustering
Gene expression
Latent Dirichlet Allocation
Machine learning
Topic modeling

Access to Document

10.1145/3107411.3107483

Cite this

Kho, S. J., Raymer, M. L., Yalamanchili, H. B., & Sheth, A. P. (2017). A novel approach for classifying gene expression data using topic modeling. In ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (pp. 388-393). (ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics). Association for Computing Machinery, Inc. https://doi.org/10.1145/3107411.3107483

A novel approach for classifying gene expression data using topic modeling. / Kho, Soon Jye; Raymer, Michael L.; Yalamanchili, Hima Bindu et al.
ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. Association for Computing Machinery, Inc, 2017. p. 388-393 (ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics).

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

Kho, SJ, Raymer, ML, Yalamanchili, HB & Sheth, AP 2017, A novel approach for classifying gene expression data using topic modeling. in ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, Association for Computing Machinery, Inc, pp. 388-393, 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2017, Boston, United States, 8/20/17. https://doi.org/10.1145/3107411.3107483

Kho SJ, Raymer ML, Yalamanchili HB, Sheth AP. A novel approach for classifying gene expression data using topic modeling. In ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. Association for Computing Machinery, Inc. 2017. p. 388-393. (ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics). doi: 10.1145/3107411.3107483

Kho, Soon Jye ; Raymer, Michael L. ; Yalamanchili, Hima Bindu et al. / A novel approach for classifying gene expression data using topic modeling. ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. Association for Computing Machinery, Inc, 2017. pp. 388-393 (ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics).

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title = "A novel approach for classifying gene expression data using topic modeling",

keywords = "Cancer, Classification, Clustering, Gene expression, Latent Dirichlet Allocation, Machine learning, Topic modeling",

author = "Kho, {Soon Jye} and Raymer, {Michael L.} and Yalamanchili, {Hima Bindu} and Sheth, {Amit P.}",

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ER -

A novel approach for classifying gene expression data using topic modeling

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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