OMIX

Predicting transcriptional responses to novel chemical perturbations using deep generative model

OMIX006910

1Summary
Title Predicting transcriptional responses to novel chemical perturbations using deep generative model
Description Understanding transcriptional responses to chemical perturbations is central to drug discovery, but exhaustive experimental high-throughput screening of disease and compound combinations is unfeasible. To overcome this limitation, we present a perturbation-conditioned deep generative model named PRnet for predicting transcriptional responses to novel chemical perturbations that were never experimentally perturbed at bulk and single-cell levels. PRnet screened four compound libraries and generated a large-scale integration atlas of perturbation profiles, including 1) 82 cell lines perturbed by 935 FDA-approved drugs, 2) 88 cell lines perturbed by 4,158 active compounds, 3) 14 CRC cell lines perturbed by 30,456 natural compounds, 4) 6 SCLC cell lines perturbed by 29,670 drug-like compounds and 5) 54 tissues perturbed by 935 FDA-approved drugs.
Organism Homo
Data Type Other Type of Genomic Data
Data Accessibility Open-access
BioProject PRJCA028278
Release Date 2024-07-22
Submitter Xiaoning Qi (qixiaoning19s@ict.ac.cn)
Organization Institute of Computing Technology, Chinese Academy of Sciences
Submission Date 2024-07-19
2Files & Download

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File ID File Title Number/Samples File Type File Size File Suffix Download Times Download
OMIX006910-01 The Inhibitor and Active Compound Metadata 1 Other Type of Genomic Data 760.34 KB csv 0
OMIX006910-02 The CREEDS Disease Metadata 1 Other Type of Genomic Data 271.17 KB csv 0
OMIX006910-03 The Sciplex Compound Metadata 1 Other Type of Genomic Data 31.73 KB csv 0
OMIX006910-04 The Natura Compound Metadata 1 Other Type of Genomic Data 10.42 MB csv 0
OMIX006910-05 The L1000 Cell Line Metadata 1 Other Type of Genomic Data 10.48 KB csv 0
OMIX006910-06 The Sciplex Cell Line Metadata 1 Other Type of Genomic Data 607 B csv 0
OMIX006910-07 Predicted Signature of Inhibitor and Active Compounds 1 Other Type of Genomic Data 181.25 MB csv 0
OMIX006910-08 Predicted Signature of SCLC Cell Lines 1 Other Type of Genomic Data 104.49 MB csv 0
OMIX006910-09 Predicted Signature of Gtex Tissues 1 Other Type of Genomic Data 11.37 GB csv 0
OMIX006910-10 Predicted Signature of FDA Approved Drugs 1 Other Type of Genomic Data 137.18 MB csv 0
OMIX006910-11 The CREEDS Disease Signature 1 Other Type of Genomic Data 18.52 MB csv 0
OMIX006910-12 The FDA Approved Drug Metadata 1 Other Type of Genomic Data 120.66 KB csv 0
OMIX006910-13 The L1000 Compound Metadata 1 Other Type of Genomic Data 3.73 MB csv 0

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