Learning signaling network structures with sparsely distributed data

Flow cytometric measurement of signaling protein abundances has proved particularly useful for elucidation of signaling pathway structure. The single cell nature of the data ensures a very large dataset size, providing a statistically robust dataset for structure learning. Moreover, the approach is...

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Bibliographic Details
Main Authors: Sachs, Karen (Author), Itani, Solomon (Contributor), Carlisle, Jennifer (Contributor), Nolan, Garry P. (Author), Pe'er, Dana (Author), Lauffenburger, Douglas A. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Mary Ann Liebert, Inc., 2010-12-17T21:50:09Z.
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