How to cite us
If you use cellXpress in your projects/publications, please cite the following primary report of cellXpress:
Spatial and phenotypic profiling of diverse cell types in highly-multiplexed fluorescence tissue images with cellXpress 2
Under review High-throughput imaging Methods
cellXpress: a fast and user-friendly software platform for profiling cellular phenotypes
The following publications used cellXpress:
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 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 imaging and artificial intelligence.
Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFa and co-treatments.
High-throughput imaging-based nephrotoxicity prediction for xenobiotics with diverse chemical structures
Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins