Unbiased reconstruction of a mammalian transcriptional network mediating the differential response to pathogens
Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to der...
Main Authors: | Amit, Ido, Guttman, Mitchell, Leite, Ana Paula, Regev, Aviv, Garber, Manuel, Chevrier, Nicolas, Donner, Yoni, Eisenhaure, Thomas, Grenier, Jennifer K., Li, Weibo, Zuk, Or, Schubert, Lisa A., Birditt, Brian, Shay, Tal, Goren, Alon, Zhang, Xiaolan, Smith, Zachary, Deering, Raquel, McDonald, Rebecca C., Cabili, Moran N., Bernstein, Bradley E., Rinn, John L., Meissner, Alexander, Root, David E., Hacohen, Nir |
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Other Authors: | Massachusetts Institute of Technology. Computational and Systems Biology Program |
Format: | Article |
Language: | en_US |
Published: |
American Association for the Advancement of Science (AAAS)
2014
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Online Access: | http://hdl.handle.net/1721.1/85204 https://orcid.org/0000-0001-5773-3211 https://orcid.org/0000-0001-8567-2049 |
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