Learning structure in gene expression data using deep architectures, with an application to gene clustering

Aman Gupta; Haohan Wang; Madhavi Ganapathiraju

doi:10.1109/BIBM.2015.7359871

Learning structure in gene expression data using deep architectures, with an application to gene clustering

Aman Gupta, Haohan Wang, Madhavi Ganapathiraju

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

Abstract

Genes play a central role in all biological processes. DNA microarray technology has made it possible to study the expression behavior of thousands of genes in one go. Often, gene expression data is used to generate features for supervised and unsupervised learning tasks. At the same time, advances in the field of deep learning have made available a plethora of architectures. In this paper, we use deep architectures pre-trained in an unsupervised manner using denoising autoencoders as a preprocessing step for a popular unsupervised learning task. Denoising autoencoders (DA) can be used to learn a compact representation of input, and have been used to generate features for further supervised learning tasks. We propose that our deep architectures can be treated as empirical versions of Deep Belief Networks (DBNs). We use our deep architectures to regenerate gene expression time series data for two different data sets. We test our hypothesis on two popular datasets for the unsupervised learning task of clustering and find promising improvements in performance.

Original language	English (US)
Title of host publication	Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Editors	lng. Matthieu Schapranow, Jiayu Zhou, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Satoru Miyano, Illhoi Yoo, Brian Pierce, Amarda Shehu, Vijay K. Gombar, Brian Chen, Vinay Pai, Jun Huan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1328-1335
Number of pages	8
ISBN (Electronic)	9781467367981
DOIs	https://doi.org/10.1109/BIBM.2015.7359871
State	Published - Dec 16 2015
Externally published	Yes
Event	IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States Duration: Nov 9 2015 → Nov 12 2015

Conference

Conference	IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Country/Territory	United States
City	Washington
Period	11/9/15 → 11/12/15

Keywords

autoencoders
deep learning
gene clustering
gene expression

ASJC Scopus subject areas

Software
Artificial Intelligence
Health Informatics
Biomedical Engineering

Online availability

10.1109/BIBM.2015.7359871

Library availability

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Gupta, A., Wang, H., & Ganapathiraju, M. (2015). Learning structure in gene expression data using deep architectures, with an application to gene clustering. In L. M. Schapranow, J. Zhou, X. T. Hu, B. Ma, S. Rajasekaran, S. Miyano, I. Yoo, B. Pierce, A. Shehu, V. K. Gombar, B. Chen, V. Pai, & J. Huan (Eds.), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 (pp. 1328-1335). Article 7359871 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2015.7359871

Learning structure in gene expression data using deep architectures, with an application to gene clustering. / Gupta, Aman; Wang, Haohan; Ganapathiraju, Madhavi.
Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. ed. / lng. Matthieu Schapranow; Jiayu Zhou; Xiaohua Tony Hu; Bin Ma; Sanguthevar Rajasekaran; Satoru Miyano; Illhoi Yoo; Brian Pierce; Amarda Shehu; Vijay K. Gombar; Brian Chen; Vinay Pai; Jun Huan. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1328-1335 7359871.

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

Gupta, A, Wang, H & Ganapathiraju, M 2015, Learning structure in gene expression data using deep architectures, with an application to gene clustering. in LM Schapranow, J Zhou, XT Hu, B Ma, S Rajasekaran, S Miyano, I Yoo, B Pierce, A Shehu, VK Gombar, B Chen, V Pai & J Huan (eds), Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015., 7359871, Institute of Electrical and Electronics Engineers Inc., pp. 1328-1335, IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, Washington, United States, 11/9/15. https://doi.org/10.1109/BIBM.2015.7359871

Gupta A, Wang H, Ganapathiraju M. Learning structure in gene expression data using deep architectures, with an application to gene clustering. In Schapranow LM, Zhou J, Hu XT, Ma B, Rajasekaran S, Miyano S, Yoo I, Pierce B, Shehu A, Gombar VK, Chen B, Pai V, Huan J, editors, Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1328-1335. 7359871 doi: 10.1109/BIBM.2015.7359871

Gupta, Aman ; Wang, Haohan ; Ganapathiraju, Madhavi. / Learning structure in gene expression data using deep architectures, with an application to gene clustering. Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015. editor / lng. Matthieu Schapranow ; Jiayu Zhou ; Xiaohua Tony Hu ; Bin Ma ; Sanguthevar Rajasekaran ; Satoru Miyano ; Illhoi Yoo ; Brian Pierce ; Amarda Shehu ; Vijay K. Gombar ; Brian Chen ; Vinay Pai ; Jun Huan. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1328-1335

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Learning structure in gene expression data using deep architectures, with an application to gene clustering

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ASJC Scopus subject areas

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