cellXpress: a fast and user-friendly software platform for profiling cellular phenotypes
How to cite us
If you use cellXpress in your projects/publications, please cite the following primary report of cellXpress:
The following publications used cellXpress:
Spatial heterogeneity, stromal phenotypes, and therapeutic vulnerabilities in colorectal cancer peritoneal metastasis
Tumor immune microenvironment delineates progression trajectories of distinct nasopharyngeal carcinoma phenotypes
Integration of new approach methods for the assessment of data-poor chemicals
Choice of PD-L1 immunohistochemistry assay influences clinical eligibility for gastric cancer immunotherapy
627 ImmunoAtlas: an online public portal for sharing, visualizing, and referencing multiplex immunohistochemistry/ immunofluorescence (mIHC/IF) images and results for immuno-oncology
Optimum concentration–response curve metrics for supervised selection of discriminative cellular phenotypic endpoints for chemical hazard assessment
Predicting direct hepatocyte toxicity in humans by combining High-throughput cellular imaging of HepaRG cells and machine learning-based phenotypic profiling
A case study with triazole fungicides to explore practical application of next generation hazard assessment methods for human health.
Utility of in vitro bioactivity as a lower bound estimate of in vivo adverse effect levels and in risk-based prioritization.
Building predictive in vitro pulmonary toxicity assays using High-throughput cellular imaging and artificial intelligence.
Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFa and co-treatments.
High-throughput cellular imaging-based nephrotoxicity prediction for xenobiotics with diverse chemical structures
Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins