Integrative clustering of multi-level ‘omic data based on non-negative matrix factorization algorithm-Reference-Cited by-同舟云学术

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Integrative clustering of multi-level ‘omic data based on non-negative matrix factorization algorithm

Published:2017-05-01 Issue:5 Volume:12 Page:e0176278
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Chalise Prabhakar,Fridley Brooke L.

Funder

National Institutes of Health

Pilot project award supported by University of Kansas Cancer Center

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference45 articles.

1. Principles and methods of integrative genomic analyses in cancer;VN Kristensen;Nat Rev Cancer,2014

2. Integrative clustering methods for high-dimensional molecular data;P Chalise;Translational cancer research,2014

3. Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis;R Shen;Bioinformatics,2009

4. Pattern discovery and cancer gene identification in integrated cancer genomic data;Q Mo;Proceedings of the National Academy of Sciences of the United States of America,2013

5. Integrative Model-Based Clustering of Microarray Methylation and Expression Data;M Kormaksson;Ann Appl Stat,2012

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