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Cytoscape Automation: empowering workflow-based network analysis

Genome biology · 2019 · Vol. 20(1) · pp. 185–185
David OtasekJohn H. MorrisJorge BouçasAlexander R. PicoBarry Demchak

Abstract

Cytoscape is one of the most successful network biology analysis and visualization tools, but because of its interactive nature, its role in creating reproducible, scalable, and novel workflows has been limited. We describe Cytoscape Automation (CA), which marries Cytoscape to highly productive workflow systems, for example, Python/R in Jupyter/RStudio. We expose over 270 Cytoscape core functions and 34 Cytoscape apps as REST-callable functions with standardized JSON interfaces backed by Swagger documentation. Independent projects to create and publish Python/R native CA interface libraries have reached an advanced stage, and a number of automation workflows are already published.

Bioinformatics and Genomic NetworksScientific Computing and Data ManagementCell Image Analysis TechniquesWorkflowPython (programming language)JSONDocumentationComputer scienceAutomationBiologyWorld Wide WebData scienceSoftware engineering

MeSH terms

AutomationSoftwareGene Regulatory NetworksWorkflowMolecular Sequence Annotation

Funding

  • National Human Genome Research Institute
  • National Institute of General Medical Sciences
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