Research ExplorerPublicationsInference of differential key regulatory networks and mechan...

Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet

Standard

Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet. / Oubounyt, Mhaned; Adlung, Lorenz; Patroni, Fabio; Wenke, Nina Kerstin; Maier, Andreas; Hartung, Michael; Baumbach, Jan; Elkjaer, Maria L.

In: BIOINFORMATICS, Vol. 39, No. 11, btad644, 01.11.2023.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Oubounyt, M, Adlung, L, Patroni, F, Wenke, NK, Maier, A, Hartung, M, Baumbach, J & Elkjaer, ML 2023, 'Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet', BIOINFORMATICS, vol. 39, no. 11, btad644. https://doi.org/10.1093/bioinformatics/btad644

APA

Oubounyt, M., Adlung, L., Patroni, F., Wenke, N. K., Maier, A., Hartung, M., Baumbach, J., & Elkjaer, M. L. (2023). Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet. BIOINFORMATICS, 39(11), [btad644]. https://doi.org/10.1093/bioinformatics/btad644

Vancouver

Oubounyt M, Adlung L, Patroni F, Wenke NK, Maier A, Hartung M et al. Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet. BIOINFORMATICS. 2023 Nov 1;39(11). btad644. https://doi.org/10.1093/bioinformatics/btad644

Bibtex

@article{0e16e08f4f4546dfa4ffb1b51fe0564e,
title = "Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet",
abstract = "MOTIVATION: The reconstruction of small key regulatory networks that explain the differences in the development of cell (sub)types from single-cell RNA sequencing is a yet unresolved computational problem.RESULTS: To this end, we have developed SCANet, an all-in-one package for single-cell profiling that covers the whole differential mechanotyping workflow, from inference of trait/cell-type-specific gene co-expression modules, driver gene detection, and transcriptional gene regulatory network reconstruction to mechanistic drug repurposing candidate prediction. To illustrate the power of SCANet, we examined data from two studies. First, we identify the drivers of the mechanotype of a cytokine storm associated with increased mortality in patients with acute respiratory illness. Secondly, we find 20 drugs for eight potential pharmacological targets in cellular driver mechanisms in the intestinal stem cells of obese mice.AVAILABILITY AND IMPLEMENTATION: SCANet is a free, open-source, and user-friendly Python package that can be seamlessly integrated into single-cell-based systems medicine research and mechanistic drug discovery.",
keywords = "Humans, Animals, Mice, Software, Gene Expression Profiling, Sequence Analysis, RNA, Drug Repositioning, Single-Cell Gene Expression Analysis, Single-Cell Analysis, Gene Regulatory Networks",
author = "Mhaned Oubounyt and Lorenz Adlung and Fabio Patroni and Wenke, {Nina Kerstin} and Andreas Maier and Michael Hartung and Jan Baumbach and Elkjaer, {Maria L}",
note = "{\textcopyright} The Author(s) 2023. Published by Oxford University Press.",
year = "2023",
month = nov,
day = "1",
doi = "10.1093/bioinformatics/btad644",
language = "English",
volume = "39",
journal = "BIOINFORMATICS",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "11",

}

RIS

TY - JOUR

T1 - Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet

AU - Oubounyt, Mhaned

AU - Adlung, Lorenz

AU - Patroni, Fabio

AU - Wenke, Nina Kerstin

AU - Maier, Andreas

AU - Hartung, Michael

AU - Baumbach, Jan

AU - Elkjaer, Maria L

N1 - © The Author(s) 2023. Published by Oxford University Press.

PY - 2023/11/1

Y1 - 2023/11/1

N2 - MOTIVATION: The reconstruction of small key regulatory networks that explain the differences in the development of cell (sub)types from single-cell RNA sequencing is a yet unresolved computational problem.RESULTS: To this end, we have developed SCANet, an all-in-one package for single-cell profiling that covers the whole differential mechanotyping workflow, from inference of trait/cell-type-specific gene co-expression modules, driver gene detection, and transcriptional gene regulatory network reconstruction to mechanistic drug repurposing candidate prediction. To illustrate the power of SCANet, we examined data from two studies. First, we identify the drivers of the mechanotype of a cytokine storm associated with increased mortality in patients with acute respiratory illness. Secondly, we find 20 drugs for eight potential pharmacological targets in cellular driver mechanisms in the intestinal stem cells of obese mice.AVAILABILITY AND IMPLEMENTATION: SCANet is a free, open-source, and user-friendly Python package that can be seamlessly integrated into single-cell-based systems medicine research and mechanistic drug discovery.

AB - MOTIVATION: The reconstruction of small key regulatory networks that explain the differences in the development of cell (sub)types from single-cell RNA sequencing is a yet unresolved computational problem.RESULTS: To this end, we have developed SCANet, an all-in-one package for single-cell profiling that covers the whole differential mechanotyping workflow, from inference of trait/cell-type-specific gene co-expression modules, driver gene detection, and transcriptional gene regulatory network reconstruction to mechanistic drug repurposing candidate prediction. To illustrate the power of SCANet, we examined data from two studies. First, we identify the drivers of the mechanotype of a cytokine storm associated with increased mortality in patients with acute respiratory illness. Secondly, we find 20 drugs for eight potential pharmacological targets in cellular driver mechanisms in the intestinal stem cells of obese mice.AVAILABILITY AND IMPLEMENTATION: SCANet is a free, open-source, and user-friendly Python package that can be seamlessly integrated into single-cell-based systems medicine research and mechanistic drug discovery.

KW - Humans

KW - Animals

KW - Mice

KW - Software

KW - Gene Expression Profiling

KW - Sequence Analysis, RNA

KW - Drug Repositioning

KW - Single-Cell Gene Expression Analysis

KW - Single-Cell Analysis

KW - Gene Regulatory Networks

U2 - 10.1093/bioinformatics/btad644

DO - 10.1093/bioinformatics/btad644

M3 - SCORING: Journal article

C2 - 37862243

VL - 39

JO - BIOINFORMATICS

JF - BIOINFORMATICS

SN - 1367-4803

IS - 11

M1 - btad644

ER -