Predicting cellular responses to complex perturbations in high‐throughput screens

Recent advances in multiplexed single‐cell transcriptomics experiments facilitate the high‐throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible. Therefore, computational methods are needed to predi...

Full description

Saved in:

Bibliographic Details
Published in:	Molecular systems biology 2023-06, Vol.19 (6), p.e11517-n/a
Main Authors:	Lotfollahi, Mohammad, Klimovskaia Susmelj, Anna, De Donno, Carlo, Hetzel, Leon, Ji, Yuge, Ibarra, Ignacio L, Srivatsan, Sanjay R, Naghipourfar, Mohsen, Daza, Riza M, Martin, Beth, Shendure, Jay, McFaline‐Figueroa, Jose L, Boyeau, Pierre, Wolf, F Alexander, Yakubova, Nafissa, Günnemann, Stephan, Trapnell, Cole, Lopez‐Paz, David, Theis, Fabian J
Format:	Article
Language:	English
Subjects:	Combinatorial analysis Computational Biology Datasets Design of experiments Drug dosages Drugs EMBO10 EMBO22 Gene expression Gene Expression Profiling generative modeling Genetic diversity High-throughput screening High-Throughput Screening Assays machine learning Modularity Neural networks Perturbation perturbation prediction Photovoltaic cells Preprints Single-Cell Gene Expression Analysis single‐cell transcriptomics Therapeutic applications Transcriptomics
Citations:	Items that this one cites Items that cite this one
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!