A Novel Approach for Classifying Gene Expression Data using Topic Modeling-Reference-Cited by-同舟云学术

A Novel Approach for Classifying Gene Expression Data using Topic Modeling

Published:2017-08-20 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics
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Author:

Kho Soon Jye¹,Yalamanchili Hima Bindu¹,Raymer Michael L.¹,Sheth Amit P.¹

Affiliation:

1. Wright State University, Dayton, OH, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3107411.3107483

Reference28 articles.

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3. Manuele Bicego Pietro Lovato Barbara Oliboni and Alessandro Perina 2010. Expression microarray classification using topic models Proceedings of the 2010 ACM Symposium on Applied Computing. ACM 1516--1520. 10.1145/1774088.1774415 Manuele Bicego Pietro Lovato Barbara Oliboni and Alessandro Perina 2010. Expression microarray classification using topic models Proceedings of the 2010 ACM Symposium on Applied Computing. ACM 1516--1520. 10.1145/1774088.1774415

4. Halil Bisgin Zhichao Liu Hong Fang Xiaowei Xu and Weida Tong 2011. Mining FDA drug labels using an unsupervised learning technique-topic modeling. BMC bioinformatics Vol. 12 10 (2011) S11. Halil Bisgin Zhichao Liu Hong Fang Xiaowei Xu and Weida Tong 2011. Mining FDA drug labels using an unsupervised learning technique-topic modeling. BMC bioinformatics Vol. 12 10 (2011) S11.

5. Pattern recognition;Bishop Christopher M;Machine Learning,2006

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