Cytoscape is an open-source software environment for integrating biomolecular interaction networks with high-throughput expression data and other molecular states. It is designed to help researchers analyze complex biological systems by combining network data with functional annotations and experimental data. The software provides basic functionality for network layout, querying, and integrating data with expression profiles, phenotypes, and other molecular states. It is extensible through a plug-in architecture, allowing for the development of additional computational analyses and features. Cytoscape's core functionality includes network layout algorithms, attribute-to-visual mapping, and graph selection and filtering. It supports the integration of molecular interaction data with functional annotations, enabling the visualization and analysis of complex biological networks. The software can be used to identify significant interaction pathways, organize network layouts based on functional attributes, and simulate biochemical models. The paper describes three case studies of Cytoscape's applications: (1) using the ActiveModules plug-in to identify pathways and protein complexes activated by genetic perturbations and environmental stimuli; (2) constructing and analyzing a combined functional/physical network for Halobacterium; and (3) stochastic simulation of the λ phage life cycle using the Systems Biology Workbench. These case studies demonstrate Cytoscape's ability to integrate and analyze complex biological data, providing insights into cellular processes and regulatory mechanisms. The paper also discusses the importance of integrating molecular interaction data with functional annotations and experimental data in systems biology. It highlights the need for flexible and open-source software that can bridge high-level interaction networks with lower-level physico-chemical models. Cytoscape is positioned as a key tool for this integration, with ongoing efforts to connect it with databases such as DIP, expression databases such as GEO, and annotation ontologies such as GO. The authors conclude that Cytoscape is a powerful tool for systems biology research, enabling the analysis of complex biological networks and the integration of diverse data types. Future directions include expanding Cytoscape's capabilities to connect with more databases and further exploring mechanisms for bridging high-level interaction networks with lower-level models. The software is supported by an active research community, with ongoing development and contributions from researchers and developers.Cytoscape is an open-source software environment for integrating biomolecular interaction networks with high-throughput expression data and other molecular states. It is designed to help researchers analyze complex biological systems by combining network data with functional annotations and experimental data. The software provides basic functionality for network layout, querying, and integrating data with expression profiles, phenotypes, and other molecular states. It is extensible through a plug-in architecture, allowing for the development of additional computational analyses and features. Cytoscape's core functionality includes network layout algorithms, attribute-to-visual mapping, and graph selection and filtering. It supports the integration of molecular interaction data with functional annotations, enabling the visualization and analysis of complex biological networks. The software can be used to identify significant interaction pathways, organize network layouts based on functional attributes, and simulate biochemical models. The paper describes three case studies of Cytoscape's applications: (1) using the ActiveModules plug-in to identify pathways and protein complexes activated by genetic perturbations and environmental stimuli; (2) constructing and analyzing a combined functional/physical network for Halobacterium; and (3) stochastic simulation of the λ phage life cycle using the Systems Biology Workbench. These case studies demonstrate Cytoscape's ability to integrate and analyze complex biological data, providing insights into cellular processes and regulatory mechanisms. The paper also discusses the importance of integrating molecular interaction data with functional annotations and experimental data in systems biology. It highlights the need for flexible and open-source software that can bridge high-level interaction networks with lower-level physico-chemical models. Cytoscape is positioned as a key tool for this integration, with ongoing efforts to connect it with databases such as DIP, expression databases such as GEO, and annotation ontologies such as GO. The authors conclude that Cytoscape is a powerful tool for systems biology research, enabling the analysis of complex biological networks and the integration of diverse data types. Future directions include expanding Cytoscape's capabilities to connect with more databases and further exploring mechanisms for bridging high-level interaction networks with lower-level models. The software is supported by an active research community, with ongoing development and contributions from researchers and developers.