SUMMARY: Cells are organized as a hierarchy of macromolecular assemblies, ranging from small protein complexes to entire organelles. Various technologies have been developed to elucidate subcellular architecture at different scales, such as mass spectrometry approaches for mapping protein biophysical interactions and immunofluorescence imaging for mapping protein localization. We present the Cell Mapping Toolkit, which is designed to systematically integrate data from different modalities into unified hierarchical maps of subcellular organization. The toolkit facilitates an end-to-end pipeline including processing datasets, integrating modalities, and visualizing the final cell map with rich metadata including provenance documentation at each step. The Cell Mapping Toolkit provides researchers with tools for analyzing, integrating, and visualizing diverse protein datasets in a robust and reproducible framework. AVAILABILITY AND IMPLEMENTATION: The code is freely available and is hosted on GitHub at https://github.com/idekerlab/cellmaps_pipeline. Comprehensive documentation and practical examples are provided at https://cellmaps-pipeline.readthedocs.io/.

SUMMARY: Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualization software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js. This update describes new features and enhancements introduced over many new versions from 2015 to 2022. AVAILABILITY AND IMPLEMENTATION: Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The investigation of sets of genes using biological pathways is a common task for researchers and is supported by a wide variety of software tools. This type of analysis generates hypotheses about the biological processes that are active or modulated in a specific experimental context. RESULTS: The Network Data Exchange Integrated Query (NDEx IQuery) is a new tool for network and pathway-based gene set interpretation that complements or extends existing resources. It combines novel sources of pathways, integration with Cytoscape, and the ability to store and share analysis results. The NDEx IQuery web application performs multiple gene set analyses based on diverse pathways and networks stored in NDEx. These include curated pathways from WikiPathways and SIGNOR, published pathway figures from the last 27 years, machine-assembled networks using the INDRA system, and the new NCI-PID v2.0, an updated version of the popular NCI Pathway Interaction Database. NDEx IQuery's integration with MSigDB and cBioPortal now provides pathway analysis in the context of these two resources. AVAILABILITY AND IMPLEMENTATION: NDEx IQuery is available at https://www.ndexbio.org/iquery and is implemented in Javascript and Java.