Predicting compound activity from phenotypic profiles and chemical structures
Experimental assays are used to determine if compounds cause a desired activity in cells. Here the authors demonstrate that computational methods can predict compound bioactivity given their chemical structure, imaging and gene expression data from historic screening libraries.
Main Authors: | Nikita Moshkov, Tim Becker, Kevin Yang, Peter Horvath, Vlado Dancik, Bridget K. Wagner, Paul A. Clemons, Shantanu Singh, Anne E. Carpenter, Juan C. Caicedo |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-04-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-023-37570-1 |
Similar Items
-
Learning representations for image-based profiling of perturbations
by: Nikita Moshkov, et al.
Published: (2024-02-01) -
Addendum: High-resolution specificity profiling and off-target prediction for site-specific DNA recombinases
by: Jeffrey L. Bessen, et al.
Published: (2019-07-01) -
Quantitative-Proteomic Comparison of Alpha and Beta Cells to Uncover Novel Targets for Lineage Reprogramming
by: Choudhary, Amit, et al.
Published: (2014) -
Quantitative-proteomic comparison of alpha and Beta cells to uncover novel targets for lineage reprogramming.
by: Amit Choudhary, et al.
Published: (2014-01-01) -
Capturing single-cell heterogeneity via data fusion improves image-based profiling
by: Mohammad H. Rohban, et al.
Published: (2019-05-01)