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84942 |
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|a dc
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|a Kim, Harold D.
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|a Massachusetts Institute of Technology. Department of Biology
|e contributor
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|a Regev, Aviv
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|a Shay, Tal
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|a Shay, Tal
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|a O'Shea, Erin K.
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|a Regev, Aviv
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|a Transcriptional Regulatory Circuits: Predicting Numbers from Alphabets
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|b American Association for the Advancement of Science (AAAS),
|c 2014-02-14T14:32:37Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/84942
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|a available in PMC 2010 January 24.
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|a Transcriptional regulatory circuits govern how cis and trans factors transform signals into messenger RNA (mRNA) expression levels. With advances in quantitative and high-throughput technologies that allow measurement of gene expression state in different conditions, data that can be used to build and test models of transcriptional regulation is being generated at a rapid pace. Here, we review experimental and computational methods used to derive detailed quantitative circuit models on a small scale and cruder, genome-wide models on a large scale. We discuss the potential of combining small- and large-scale approaches to understand the working and wiring of transcriptional regulatory circuits.
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|a Howard Hughes Medical Institute
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|a National Institutes of Health (U.S.) (NIH GM51377)
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|a National Institutes of Health (U.S.) (NIH DP1-OD00395)
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|a Burroughs Wellcome Fund (Career Award at the Scientific Interface)
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|a ofI (Firm)
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|a en_US
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|a Article
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|t Science
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