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From Correlation to Causality: Statistical Approaches to Learning Regulatory Relationships in Large-Scale Biomolecular Investigations.
Ness, Robert O; Sachs, Karen; Vitek, Olga.
Affiliation
  • Ness RO; Department of Statistics, Purdue University , West Lafayette, Indiana 47907-2066, United States.
  • Sachs K; College of Science, College of Computer and Information Science, Northeastern University , Boston, Massachusetts 02115, United States.
  • Vitek O; School of Medicine, Stanford University , Palo Alto, California 94305, United States.
J Proteome Res ; 15(3): 683-90, 2016 Mar 04.
Article in En | MEDLINE | ID: mdl-26731284
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Causality / Models, Statistical / Computational Biology / Gene Regulatory Networks Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Animals / Humans Language: En Journal: J Proteome Res Journal subject: BIOQUIMICA Year: 2016 Document type: Article Affiliation country: Country of publication:
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Causality / Models, Statistical / Computational Biology / Gene Regulatory Networks Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Animals / Humans Language: En Journal: J Proteome Res Journal subject: BIOQUIMICA Year: 2016 Document type: Article Affiliation country: Country of publication: