Integrating and mining the chromatin landscape of cell-type specificity using self-organizing maps

Integrating and mining the chromatin landscape of cell-type specificity using self-organizing maps

We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and mine diverse genomics data types, including complex chromatin signatures. A fine-grained SOM was trained on 72 ChIP-seq histone modifications and DNase-seq data sets from six biologically diverse cel...

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Bibliographic Details
Main Authors: Kellis, Manolis (Contributor), Mortazavi, Ali (Author), Pepke, Shirley (Author), Jansen, Camden (Author), Marinov, Georgi K. (Author), Ernst, Jason (Author), Hardison, Ross C. (Author), Myers, Richard M. (Author), Wold, Barbara J. (Author)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Cold Spring Harbor Laboratory Press, 2014-03-17T14:47:28Z.
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