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http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html
The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape''''s versatile visualization environment to produce an intuitive and customizable visual representation of the results. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: BiNGO: A Biological Networks Gene Ontology tool (RRID:SCR_005736) Copy
https://github.com/nolanlab/cytospade
Cytoscape plugin that provides a high-performance implementation of an interface for the Spanning-tree Progression Analysis of Density-normalized Events (SPADE) algorithm for tree-based analysis and visualization of high-dimensional cytometry data.
Proper citation: CytoSPADE (RRID:SCR_001457) Copy
http://www.ici.upmc.fr/cluego/
A Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: ClueGO (RRID:SCR_005748) Copy
http://portal.ncibi.org/gateway/mimiplugin.html
The Cytoscape MiMI Plugin is an open source interactive visualization tool that you can use for analyzing protein interactions and their biological effects. The Cytoscape MiMI Plugin couples Cytoscape, a widely used software tool for analyzing bimolecular networks, with the MiMI database, a database that uses an intelligent deep-merging approach to integrate data from multiple well-known protein interaction databases. The MiMI database has data on 119,880 molecules, 330,153 interactions, and 579 complexes. By querying the MiMI database through Cytoscape you can access the integrated molecular data assembled in MiMI and retrieve interactive graphics that display protein interactions and details on related attributes and biological concepts. You can interact with the visualization by expanding networks to the next nearest neighbors and zooming and panning to relationships of interest. You also can perceptually encode nodes and links to show additional attributes through color, size and the visual cues. You can edit networks, link out to other resources and tools, and access information associated with interactions that has been mined and summarized from the research literature information through a biology natural language processing database (BioNLP) and a multi-document summarization system, MEAD. Additionally, you can choose sub-networks of interest and use SAGA, a graph matching tool, to match these sub-networks to biological pathways.
Proper citation: MiMI Plugin for Cytoscape (RRID:SCR_003424) Copy
http://apps.cytoscape.org/apps/pepper
A Cytoscape app designed to identify protein pathways / complexes as densely connected subnetworks from seed lists of proteins derived from pull-down assays (i.e AP-MS...).
Proper citation: PEPPER (RRID:SCR_000431) Copy
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