{"categories":[{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"},{"label":"Image Processing","url":"https://skillfed.io/packages/category/scientific-engineering-image-processing"}],"enrichment":{"capability":"PyCAT-Napari is a napari-based desktop application for detecting, measuring, and analyzing biomolecular condensates in fluorescence and brightfield microscopy images, with support for 2D, Z-stack, and time-series data.","skillfed_tags":["microscopy","image-analysis","gui-application"],"use_cases":["Segment and measure fluorescent biomolecular condensates in fixed or live-cell images without writing code.","Analyze colocalization between two or more fluorescent channels using object-based and pixel-wise metrics.","Track condensate trajectories over time and measure fusion kinetics, diffusion, and coarsening mechanisms.","Estimate saturation concentration (C_sat) from intensity distributions and dilution-series experiments.","Process large time-series or Z-stack acquisitions in batch mode by recording GUI actions and replaying them across a folder.","Measure morphological complexity (fractal dimension, lacunarity) and spatial organization (DBSCAN clustering, Voronoi) of condensate ensembles."],"what_it_does":"PyCAT-Napari is a low/no-code desktop application for analyzing biomolecular condensates in microscopy images. Built on napari, it provides a graphical interface to segment condensates, measure their properties (area, intensity, shape, texture), perform colocalization analysis, track trajectories over time, and estimate biophysical parameters like saturation concentration and diffusion rates. It handles 2D single images, Z-stacks, and time-series acquisitions in both fluorescence and brightfield modalities.\n\nThe package bundles 28 runtime dependencies\u2014including numpy, scipy, scikit-image, torch, cellpose, and PyQt5\u2014to deliver image processing, machine-learning-based segmentation, statistical analysis, and a full GUI. It is designed for researchers without programming experience, offering batch processing via JSON configuration and specialized pipelines for cellular condensates, in-vitro droplets, time-series analysis, and fibril structures. Optional GPU acceleration is available for Cellpose segmentation and morphological operations.","worth_installing":"Yes, if you are a biologist or microscopist analyzing condensates and want a low-code GUI tool. The package is actively maintained, permissively licensed, has no known vulnerabilities, and offers a comprehensive feature set tailored to condensate research. Install friction is low for a pure-Python package, though the 28 dependencies mean a dedicated environment is prudent. Not suitable if you need Python 3.11 or earlier, or if you prefer a command-line or programmatic API over a GUI."},"id":"pycat-napari","links":{"html":"https://skillfed.io/packages/pycat-napari","md":"https://skillfed.io/packages/pycat-napari.md","pypi":"https://pypi.org/project/pycat-napari/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-06","license_spdx":null,"license_treatment":"permissive","name":"pycat-napari","python_support":"capped_below_current","summary":"Python Condensate Analysis Toolbox - A napari-based tool for biomolecular condensate analysis"},"popularity":{"monthly_downloads":296990,"position":7892,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.6.458"}