Identifying therapeutic targets by combining transcriptional data with ordinal clinical measurements

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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Detaylı Bibliyografya
Asıl Yazarlar: 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
Diğer Yazarlar: Massachusetts Institute of Technology. Department of Biological Engineering
Materyal Türü: Makale
Baskı/Yayın Bilgisi: Nature Publishing Group 2017
Online Erişim: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

Internet

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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