MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets

MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundre...

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Bibliographic Details
Main Authors: Naegle, Kristen Marie, White, Forest M., Welsch, Roy E, Yaffe, Michael B, Lauffenburger, Douglas A
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering
Format: Article
Language:en_US
Published: Public Library of Science 2011
Online Access:http://hdl.handle.net/1721.1/66157
https://orcid.org/0000-0002-1545-1651
https://orcid.org/0000-0002-9038-1622
https://orcid.org/0000-0002-9547-3251

Internet

http://hdl.handle.net/1721.1/66157
https://orcid.org/0000-0002-1545-1651
https://orcid.org/0000-0002-9038-1622
https://orcid.org/0000-0002-9547-3251

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