Related Experiment Video
Updated: Oct 17, 2026

10:37
Single-cell Microfluidic Analysis of Bacillus subtilis
Published on: January 26, 2018
Learning how single cells respond to perturbations
Ekin Deniz Aksu1, Bonnie Berger2
1Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany; Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA.
Molecular Cell
|October 15, 2026
Abstract:
In a recent issue of Cell, Adduri et al.1 introduce State, a machine learning model that generalizes across different cellular contexts and predicts how single-cell transcriptomes respond to genetic or chemical perturbations.
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The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity.
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