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Using Kepler for Tool Integration in Microarray Analysis Workflows.
Gan, Zhuohui; Stowe, Jennifer C; Altintas, Ilkay; McCulloch, Andrew D; Zambon, Alexander C.
Afiliação
  • Gan Z; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
  • Stowe JC; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
  • Altintas I; San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, USA.
  • McCulloch AD; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
  • Zambon AC; Departments of Pharmacology, University of California, San Diego, La Jolla, CA, USA.
Procedia Comput Sci ; 29: 2162-2167, 2014.
Article em En | MEDLINE | ID: mdl-26605000
Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2014 Tipo de documento: Article