The paper introduces a dataset of cell morphology images treated with matched chemical and genetic perturbations and evaluates methods for identifying perturbation similarities.

Nature Methods · Apr 9, 2024Peer-reviewedBioinformatics

JUMP Cell Painting chemical dataset: Morphological map of 115,796 compounds in human cells

Srinivas Niranj Chandrasekaran, Jeanelle Ackerman, Eric Alix, Dale Michael Ando, John Arévalo, Melissa Bennion, Nicolas Boisseau, Adriana Borowa, Justin D. Boyd, Laurent Brino, Patrick J. Byrne, Hugo Ceulemans, Carolyn Ch’ng, Beth A. Cimini, Djork-Arné Clevert, , Anne Elizabeth Carpenter

Cell Painting images and profiles for 115,796 compounds in U2OS cells from 12 laboratories; 15.2% of analyzed compounds are phenotypically active, and cross-laboratory replicates cut reference-compound activity by 34%.

bioRxiv · Mar 23, 2023 · PreprintBioinformatics✦ In-depth digest

SUMO - In Silico Sequence Assessment Using Multiple Optimization Parameters

Andreas Evers, Shipra Malhotra, Wolf-Guido Bolick, Ahmad Najafian, Maria Borisovska, Shira Warszawski, Yves Fomekong‐Nanfack, Daniel Kühn, Friedrich Rippmann, Alejandro Crespo, Vanita D. Sood

The paper introduces a computational method to assess and rank antibody and VHH sequences based on developability, diversity, and optimization potential using in silico analysis.

bioRxiv · Nov 19, 2022 · PreprintBioinformatics