JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data-Reference-Cited by-同舟云学术

JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data

Published:2017-06-05 Issue:19 Volume:33 Page:3080-3087
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Ji Jiadong¹,He Di²,Feng Yang³,He Yong¹,Xue Fuzhong⁴,Xie Lei²⁵

Affiliation:

1. Department of Mathematical Statistics, School of Statistics, Shandong University of Finance and Economics, Jinan, China

2. Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY, USA

3. Department of Statistics, Columbia University, New York, NY, USA

4. Department of Biostatistics, School of Public Health, Shandong University, Jinan, China

5. Department of Computer Science, Hunter College, The City University of New York, NY, USA

Funder

National Institute on Minority Health and Health Disparities of the National Institutes of Health

National Science Foundation

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/33/19/3080/25164885/btx360.pdf

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