Sparse robust matrix tri-factorization with application to cancer genomics

Seung Jun Kim; Tae Hyun Hwang; Georgios B Giannakis

doi:10.1109/CIP.2012.6232906

Sparse robust matrix tri-factorization with application to cancer genomics

Seung Jun Kim
, Tae Hyun Hwang
, Georgios B Giannakis

Electrical and Computer Engineering

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

7 Scopus citations

Abstract

Nonnegative matrix tri-factorization (NMTF) X ≈ FSG ^T with all matrices nonnegative can reveal simultaneous row and column clusters of X, as well as the associations among the two. In this work, a sparsity-promoting variant is proposed and a simple multiplicative algorithm is developed. The resulting sparse NMTF is further robustified to cope with presence of outliers in the data. A synthetic example illustrates the efficacy of the method. A novel application to cancer patient clustering and pathway analysis is presented using real datasets.

Original language	English (US)
Title of host publication	2012 3rd International Workshop on Cognitive Information Processing, CIP 2012
DOIs	https://doi.org/10.1109/CIP.2012.6232906
State	Published - 2012
Event	2012 3rd International Workshop on Cognitive Information Processing, CIP 2012 - Baiona, Spain Duration: May 28 2012 → May 30 2012

Publication series

Name	2012 3rd International Workshop on Cognitive Information Processing, CIP 2012

Other

Other	2012 3rd International Workshop on Cognitive Information Processing, CIP 2012
Country/Territory	Spain
City	Baiona
Period	5/28/12 → 5/30/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/CIP.2012.6232906

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Sparse robust matrix tri-factorization with application to cancer genomics. / Kim, Seung Jun; Hwang, Tae Hyun; Giannakis, Georgios B.
2012 3rd International Workshop on Cognitive Information Processing, CIP 2012. 2012. 6232906 (2012 3rd International Workshop on Cognitive Information Processing, CIP 2012).

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

Kim, SJ, Hwang, TH & Giannakis, GB 2012, Sparse robust matrix tri-factorization with application to cancer genomics. in 2012 3rd International Workshop on Cognitive Information Processing, CIP 2012., 6232906, 2012 3rd International Workshop on Cognitive Information Processing, CIP 2012, 2012 3rd International Workshop on Cognitive Information Processing, CIP 2012, Baiona, Spain, 5/28/12. https://doi.org/10.1109/CIP.2012.6232906

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abstract = "Nonnegative matrix tri-factorization (NMTF) X ≈ FSG T with all matrices nonnegative can reveal simultaneous row and column clusters of X, as well as the associations among the two. In this work, a sparsity-promoting variant is proposed and a simple multiplicative algorithm is developed. The resulting sparse NMTF is further robustified to cope with presence of outliers in the data. A synthetic example illustrates the efficacy of the method. A novel application to cancer patient clustering and pathway analysis is presented using real datasets.",

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AN - SCOPUS:84864662892

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T2 - 2012 3rd International Workshop on Cognitive Information Processing, CIP 2012

Y2 - 28 May 2012 through 30 May 2012

ER -

Sparse robust matrix tri-factorization with application to cancer genomics

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