Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study-Reference-Cited by-同舟云学术

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study

Published:2017-05-23 Issue:18 Volume:33 Page:2890-2896
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Städler Nicolas¹,Dondelinger Frank²,Hill Steven M³,Akbani Rehan⁴,Lu Yiling⁵,Mills Gordon B⁵,Mukherjee Sach⁶

Affiliation:

1. Global Pricing and Market Access, F. Hoffmann-La Roche Ltd, Basel, Switzerland

2. Lancaster Medical School, Lancaster University, Lancaster, UK

3. MRC Biostatistics Unit, University of Cambridge, Cambridge, UK

4. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

5. Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

6. German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/33/18/2890/25331732/btx322.pdf

Reference18 articles.

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2. An atlas of active enhancers across human cell types and tissues;Andersson;Nature,2014

3. A two-sample test for high-dimensional data with applications to gene-set testing;Chen;Ann. Stat,2010

4. Advantages and limitations of current network inference methods;De Smet;Nat. Rev. Microbiol,2010

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