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JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data
Jiadong Ji, Di He, View ORCID ProfileYang Feng, Yong He, Fuzhong Xue, Lei Xie
doi: https://doi.org/10.1101/099234
Jiadong Ji
1Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, China.
2Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065,USA.
Di He
3The Graduate Center, The City University of New York, New York, NY 10016, USA.
Yang Feng
4Department of Statistics, Columbia University, New York, NY 10027, USA.
Yong He
5Department of Statistics, School of Management, Fudan University, Shanghai 200433, China.
Fuzhong Xue
1Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, China.
Lei Xie
2Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065,USA.
3The Graduate Center, The City University of New York, New York, NY 10016, USA.
Posted January 09, 2017.
JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data
Jiadong Ji, Di He, Yang Feng, Yong He, Fuzhong Xue, Lei Xie
bioRxiv 099234; doi: https://doi.org/10.1101/099234
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