• Slide 1

    Fast processing speed Written in C/C++ and optimized for modern 64-bit and multi-core CPUs. Support parallel processing and dynamic job scheduling for high-throughput applications.

  • Slide 2

    Single-cell phenotype quantification Automatically identify individual cells from fluorescence microscopy images; and quantify cellular morphology, protein sub-cellular localization and other features.

  • Slide 3

    User-friendly interface Intuitive graphical user interface for interactive configuration of computational algorithms and visualization of segmentation and feature extraction results.

Cellular phenotype profiling


cellXpress

cellXpress is a cellular phenotype profiling software platform developed by the Loo Lab at the Bioinformatics Institute, A*STAR, Singapore. The platform is designed for fast and high-throughput analysis of cellular phenotypes based on microscopy images. It is especially useful for large-scale profiling of cellular responses to pharmacological compounds, gene knockdowns, and/or toxic substances.



Latest News

  • 8 March 2017 cellXpress pro 1.4.2 is available now. This is a critical update that fixes a bug in loading images with no cell. All users are recommended to update their cellXpress to this latest version.

  • 13 Feb 2017 cellXpress pro 1.4.1 is available now. This is a critical update that fixes a bug in loading images with non-zero-based channel indices. All users are recommended to update their cellXpress to this latest version.

  • 2 Feb 2017 cellXpress pro 1.4 is available now. Major improvements include automated detection of chromosomal regions, faster feature loading, and autofluorescence quantification.

Features Highlight


  1. Quantify single-cell phenotypes Single-cell phenotype quantification Automatically identify individual cells from fluorescence microscopy images; and quantify cellular morphology, protein sub-cellular localization and other features.

  2. Plate-based data organization Plate-based data organization Design to handle high volume of image data acquired from 96/384-well plates. Analyses of different fluorescent-marker configurations can be performed on the same plate data.

  3. Quick plate analysis Quick plate analysis Perform cell count and fluorescence intensity measurements over the whole plates, and visualize well-to-well trend and variability.

  4. Phenotypic profiling Phenotypic profiling Transform raw image features into discriminative profiles that can be used to characaterize changes in cellular phenotypes.