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Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer
Safiye Celik, Benjamin A Logsdon, Stephanie Battle, Charles W Drescher, Mara Rendi, Hawkins David R, Su-In Lee
doi: https://doi.org/10.1101/048215
Safiye Celik
1Department of Computer Science & Engineering, University of Washington, Seattle, WA
Benjamin A Logsdon
2Sage Bionetworks, Seattle, WA
Stephanie Battle
3Department of Genome Sciences, University of Washington, Seattle, WA
Charles W Drescher
4Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
Mara Rendi
5Department of Anatomic Pathology, University of Washington, Seattle, WA
Hawkins David R
3Department of Genome Sciences, University of Washington, Seattle, WA
6Medical Genetics, Department of Medicine, University of Washington, Seattle, WA
Su-In Lee
1Department of Computer Science & Engineering, University of Washington, Seattle, WA
3Department of Genome Sciences, University of Washington, Seattle, WA
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Posted April 13, 2016.
Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer
Safiye Celik, Benjamin A Logsdon, Stephanie Battle, Charles W Drescher, Mara Rendi, Hawkins David R, Su-In Lee
bioRxiv 048215; doi: https://doi.org/10.1101/048215
Extracting a low-dimensional description of multiple gene expression datasets reveals a potential driver for tumor-associated stroma in ovarian cancer
Safiye Celik, Benjamin A Logsdon, Stephanie Battle, Charles W Drescher, Mara Rendi, Hawkins David R, Su-In Lee
bioRxiv 048215; doi: https://doi.org/10.1101/048215
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