Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape’s software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

References in zbMATH (referenced in 77 articles )

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  1. Alberto Garcia-Robledo, Mahboobeh Zangiabady: Dash Sylvereye: A WebGL-powered Library for Dashboard-driven Visualization of Large Street Networks (2021) arXiv
  2. Guo, Q.; Sowa, A.: An almost-solvable model of complex network dynamics (2020)
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  5. Nahálková, Jarmila: The molecular mechanisms associated with PIN7, a protein-protein interaction network of seven pleiotropic proteins (2020)
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  7. Sanchez, Martin Jose Angel; Petre, Ion: Network controllability analysis of three multiple-myeloma patient genetic mutation datasets (2020)
  8. Dimitrios Michail, Joris Kinable, Barak Naveh, John V Sichi: JGraphT - A Java library for graph data structures and algorithms (2019) arXiv
  9. K. Hunter Wapman; Daniel B. Larremore: webweb: a tool for creating, displaying, and sharinginteractive network visualizations on the web (2019) not zbMATH
  10. Liang, Yulan; Kelemen, Adam; Kelemen, Arpad: Reproducibility of biomarker identifications from mass spectrometry proteomic data in cancer studies (2019)
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