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Stock, M. ; Losert, C. ; Zambon, M. ; Popp, N. ; Lubatti, G. ; Hörmanseder, E. ; Heinig, M. ; Scialdone, A.

Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data.

Mol. Syst. Biol. 21, 214-230 (2025)

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Many studies have used single-cell RNA sequencing (scRNA-seq) to infer gene regulatory networks (GRNs), which are crucial for understanding complex cellular regulation. However, the inherent noise and sparsity of scRNA-seq data present significant challenges to accurate GRN inference. This review explores one promising approach that has been proposed to address these challenges: integrating prior knowledge into the inference process to enhance the reliability of the inferred networks. We categorize common types of prior knowledge, such as experimental data and curated databases, and discuss methods for representing priors, particularly through graph structures. In addition, we classify recent GRN inference algorithms based on their ability to incorporate these priors and assess their performance in different contexts. Finally, we propose a standardized benchmarking framework to evaluate algorithms more fairly, ensuring biologically meaningful comparisons. This review provides guidance for researchers selecting GRN inference methods and offers insights for developers looking to improve current approaches and foster innovation in the field.

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Publication type Article: Journal article

Document type Review

Corresponding Author

Keywords Gene Regulatory Network Inference ; Graph Learning ; Prior Knowledge ; Single-cell Multiomics ; Single-cell Transcriptomics; Accessibility; Chromatin; Mouse

ISSN (print) / ISBN 1744-4292

e-ISSN 1744-4292

Journal Molecular Systems Biology

Quellenangaben Volume: 21, Issue: 3, Pages: 214-230

Publisher EMBO Press

Publishing Place Campus, 4 Crinan St, London, N1 9xw, England

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute of Epigenetics and Stem Cells (IES)
Institute of Computational Biology (ICB)
Institute of Functional Epigenetics (IFE)

Grants DZHK partner site project
Helmholtz Association under the joint research school "Munich School for Data Science
Joachim Herz Stiftung Add-on Fellowship for Interdisciplinary Life Science
Helmholtz Association
Deutsche Forschungsgemeinschaft
Chan Zuckerberg Foundation
Helmholtz Association ((sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic))