This study evaluates alternative dyes for image-based profiling assays, finding that some substitutions maintain performance while enabling live-cell imaging and expanded feature space.

SLAS DISCOVERY · Aug 28, 2025Peer-reviewedCell Biology

Morphological map of under- and over-expression of genes in human cells

Srinivas Niranj Chandrasekaran, Eric Alix, John Arévalo, Adriana Borowa, Patrick J. Byrne, William G Charles, Zitong Chen, Beth A. Cimini, Boxiong Deng, John G. Doench, Jessica Ewald, Briana Fritchman, Colin J. Fuller, Jedidiah Gaetz, Amy B. Goodale, , Anne Elizabeth Carpenter

The paper presents a comprehensive genetic perturbation dataset using Cell Painting to analyze gene expression effects in human cells, revealing novel gene clusters and functional relationships.

Nature Methods · Aug 1, 2025Peer-reviewedBioinformatics

A versatile information retrieval framework for evaluating profile strength and similarity

Alexandr A. Kalinin, John Arévalo, Erik Serrano, Loan Vulliard, Hillary Tsang, Michael Bornholdt, Alán F Muñoz, Suganya Sivagurunathan, Bartek P. Rajwa, Anne Elizabeth Carpenter, Gregory P. Way, Shantanu Singh

The paper introduces a statistical framework using mean average precision (mAP) to evaluate phenotypic activity and consistency in high-dimensional profiling data across various modalities and perturbation types.

Nature Communications · Jun 4, 2025Peer-reviewedBioinformatics

A label-free method to track individuals and lineages of budding cells

Julian MJ Pietsch, Alán F Muñoz, Diane-Yayra Adjavon, Iseabail Farquhar, Ivan B. N. Clark, Peter S. Swain

This paper introduces BABY, a label-free method to track budding yeast cells and estimate growth rates using machine learning, revealing sizer- and timer-controlled bud growth and Sfp1 dynamics.

eLife · Jul 7, 2023Peer-reviewedSystems Biology