Learning time-varying information flow from single-cell epithelial to mesenchymal transition data
Learning time-varying information flow from single-cell epithelial to mesenchymal transition data
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United States: Public Library of Science
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Language
English
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United States: Public Library of Science
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Contents
Cellular regulatory networks are not static, but continuously reconfigure in response to stimuli via alterations in protein abundance and confirmation. However, typical computational approaches treat them as static interaction networks derived from a single time point. Here, we provide methods for learning the dynamic modulation of relationships be...
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Full title
Learning time-varying information flow from single-cell epithelial to mesenchymal transition data
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TN_cdi_doaj_primary_oai_doaj_org_article_6996a616534f4fca87b99ae816b30485
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6996a616534f4fca87b99ae816b30485
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0203389
