Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements

The immense and growing repositories of transcriptional data may contain critical insights for developing new therapies. Current approaches to mining these data largely rely on binary classifications of disease vs. control, and are not able to incorporate measures of disease severity. We report an a...

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Bibliographic Details
Main Authors: Dunn, Denise E., Avila-Pacheco, Julian, Greengard, Paul, Clish, Clary B., Lo, Donald C., Pirhaji, Leila, Milani, Pamela, Dalin, Simona, Wassie, Brook T., Fenster, Robert, Heiman, Myriam, Fraenkel, Ernest
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering
Format: Article
Published: Nature Publishing Group 2017
Online Access:http://hdl.handle.net/1721.1/112189
https://orcid.org/0000-0001-6246-276X
https://orcid.org/0000-0003-0250-0474
https://orcid.org/0000-0001-5024-9718
https://orcid.org/0000-0002-6365-8673
https://orcid.org/0000-0001-9249-8181

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