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Branch: an interactive, web-based tool for testing hypotheses and developing predictive models.
Gangavarapu, Karthik; Babji, Vyshakh; Meißner, Tobias; Su, Andrew I; Good, Benjamin M.
Afiliação
  • Gangavarapu K; Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
  • Babji V; Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
  • Meißner T; Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
  • Su AI; Avera Health, Sioux Falls, South Dakota, USA.
  • Good BM; Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Bioinformatics ; 32(13): 2072-2074, 2016 07 01.
Article em En | MEDLINE | ID: mdl-27153723
ABSTRACT
UNLABELLED Branch is a web application that provides users with the ability to interact directly with large biomedical datasets. The interaction is mediated through a collaborative graphical user interface for building and evaluating decision trees. These trees can be used to compose and test sophisticated hypotheses and to develop predictive models. Decision trees are built and evaluated based on a library of imported datasets and can be stored in a collective area for sharing and re-use. AVAILABILITY AND IMPLEMENTATION Branch is hosted at http//biobranch.org/ and the open source code is available at http//bitbucket.org/sulab/biobranch/ CONTACTS asu@scripps.edu or bgood@scripps.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Árvores de Decisões / Pesquisa Biomédica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Árvores de Decisões / Pesquisa Biomédica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos