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DataRemix: a universal data transformation for optimal inference from gene expression datasets
View ORCID ProfileWeiguang Mao, Javad Rahimikollu, Ryan Hausler, Bernard Ng, Sara Mostafavi, Maria Chikina
doi: https://doi.org/10.1101/357467
Weiguang Mao
1Department of Computational and Systems Biology, Pittsburgh, USA
2Joint Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, USA
Javad Rahimikollu
1Department of Computational and Systems Biology, Pittsburgh, USA
Ryan Hausler
3Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, USA
Bernard Ng
4Department of Statistics, University of British Columbia, Vancouver, Canada
Sara Mostafavi
4Department of Statistics, University of British Columbia, Vancouver, Canada
5Department of Medical Genetics, University of British Columbia, Vancouver, Canada
Maria Chikina
1Department of Computational and Systems Biology, Pittsburgh, USA
2Joint Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, USA
Posted August 27, 2019.
DataRemix: a universal data transformation for optimal inference from gene expression datasets
Weiguang Mao, Javad Rahimikollu, Ryan Hausler, Bernard Ng, Sara Mostafavi, Maria Chikina
bioRxiv 357467; doi: https://doi.org/10.1101/357467
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