The premier open-source platform for complex network visualization and multi-omic data integration.
Cytoscape is a robust, open-source software platform designed for visualizing complex networks and integrating these networks with any type of attribute data. Originally created for biological research, its 2026 market position has expanded significantly into cybersecurity, social network analysis, and AI interpretability. Technically, Cytoscape is built on a modular Java architecture that supports an extensive 'App' ecosystem, allowing users to extend its core functionality with specialized algorithms for clustering, pathway analysis, and graph metrics. The platform leverages a headless API layer (CyREST), enabling seamless programmatic control via Python (py4cytoscape) and R (RCy3), which facilitates its integration into automated data science pipelines. As of 2026, Cytoscape remains the industry standard for mapping multi-dimensional datasets onto visual graphs, providing high-performance layout engines capable of handling millions of nodes and edges. Its ability to perform differential network analysis and overlay high-throughput experimental data makes it indispensable for researchers navigating the complexities of systems-level interactions in both natural and artificial environments.
A RESTful API that allows external languages like Python, R, and JavaScript to control Cytoscape programmatically.
The open-source BI platform that turns your dbt project into a governed, version-controlled analytics engine.
Convert natural language prompts into high-performance SQL for the Atlassian Data Lake.
Transform fragmented datasets into navigable, high-fidelity neural knowledge graphs for RAG orchestration.
The Business Cloud: Modernizing workflows through real-time data integration, AI, and intuitive app experiences.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A marketplace of over 300+ community-developed plugins for specialized analysis.
Dynamic mapping of data values (numeric or categorical) to visual properties of nodes and edges.
Optimized rendering engines for handling networks exceeding 100,000 nodes and edges.
Tools to compare two or more networks to identify structural or attribute differences.
Direct connectivity to public databases like STRING, GeneMANIA, and WikiPathways.
Capability to embed a sub-network inside a single node for hierarchical data representation.
Visualizing how gene expression changes affect metabolic pathways.
Registry Updated:2/7/2026
Identifying money laundering rings through transaction patterns.
Mapping lateral movement within a compromised network.