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

Open Access

Peer-reviewed

Research Article

Kristen M. Naegle,

Affiliations Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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Roy E. Welsch,

Affiliation Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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Michael B. Yaffe,

Affiliations Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
⨯
Forest M. White,

Affiliations Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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Douglas A. Lauffenburger

* E-mail: lauffen@mit.edu

Affiliation Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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Phosphorylation
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MAPK signaling cascades
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Signaling networks
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Clustering algorithms
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Proteomic databases
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Focal adhesions
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Protein domains
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Hierarchical clustering
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