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The JUMP-Cell Painting Consortium is alluded to in the Nature Reviews Drug Discovery news item, " Machine learning brings cell imaging promises into focus". The article overviews the entire field of image-based profiling and phenotype discovery, including industry and academic developments.

Congrats Eriene-Heidi Sidhom, Choah Kim, Masha Alimova and the rest of the team on the acceptance of their Braf/CoQ podocyte paper at JCI today!

Technology Networks recently published "Automating Drug Discovery With Machine Learning" by Neeta Ratanghayra and featured a section on image-based profiling for drug discovery. COBA's Anne Carpenter was featured and spoke about image-based profiling in general as well as the use of machine learning...

COBA's Anne Carpenter recently won the American Society for Cell Biology's Women in Cell Biology Mid-career Award. As part of this award, Carpenter wrote an award essay, "A well-engineered path into cell biology and academia", published in the November 30 issue of Molecular Biology of the Cell. Of...

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May 6th, 9th and 10th - Virtual Conference Check the I2K 2022 conference page for further details. Presenters, Workshops and Demos! If you would like to be a presenter or hold a workshop/demo at I2K 2022 please submit a Request to Present form.

The newly optimized version 3 of the protocol has been accepted! It is in press at Nature Protocols as Cimini et al. 2023.

Ardigen’s phenAID portal The phenAID JUMP-CP Explorer was created by the Ardigen Data Science and Software Development team to enable easy access and visualization of JUMP-CP data. The web-based application shows a phenotypic and structural representation of the data set colored by clusters. Users...

We are excited to share that the JUMP Cell Painting Datasets now include most data components from all but one of the sources for the principal dataset (cpg0016), covering 116,000 chemical and over 20,000 genetic perturbations (covering ~15,000 genes). The first draft of metadata files are available...

Thank you to all involved! As this three year project comes to a close, the whole project team wants to extend a warm thank you to all involved: more than a hundred scientists worked in nine workstreams to design, execute, and share this dataset. It took expertise across cell biology, chemistry...