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Network inference with Granger causality ensembles on single-cell transcriptomics

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Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data

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From time-series transcriptomics to gene regulatory networks: A review on inference methods

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scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data

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Gene regulatory network inference in single-cell biology

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Integration of single-cell multi-omics for gene regulatory network inference

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spliceJAC: transition genes and state‐specific gene regulation from single‐cell transcriptome data

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Network-based analysis of fluid flows: Progress and outlook

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The Importance of Computational Modeling in Stem Cell Research

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Machine learning for single-cell genomics data analysis

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LogBTF: gene regulatory network inference using Boolean threshold network model from single-cell gene expression data

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Opportunities and challenges of single-cell and spatially resolved genomics methods for neuroscience discovery

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Causal gene regulatory analysis with RNA velocity reveals an interplay between slow and fast transcription factors

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Recent advances in exploring transcriptional regulatory landscape of crops

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Single-cell gene set enrichment analysis and transfer learning for functional annotation of scRNA-seq data

Franchini, M., Pellecchia, S., Viscido, G., & Gambardella, G. (2023) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqad024 · Cited by 30

RVAgene: generative modeling of gene expression time series data

Mitra, R., & MacLean, A. L. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab260 · Cited by 27

Exploring long non-coding RNA networks from single cell omics data

Zhao, X. F., Lan, Y., & Chen, D. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.08.003 · Cited by 27

Gene Regulatory Network Inference using 3D Convolutional Neural Network

Fan, Y. B., & Ma, X. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i1.16082 · Cited by 26

A Machine Learning Approach to Simulate Gene Expression and Infer Gene Regulatory Networks

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A review on gene regulatory network reconstruction algorithms based on single cell RNA sequencing

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Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data

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Decoding brain memory formation by single-cell RNA sequencing

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Inferring single-cell gene regulatory network by non-redundant mutual information

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scMINER: a mutual information-based framework for clustering and hidden driver inference from single-cell transcriptomics data

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Optimal distance metrics for single-cell RNA-seq populationsPreprint

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Multi-omic network inference from time-series data

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Inferring gene regulatory network via fusing gene expression image and RNA-seq data

Li, X., Ma, S., Liu, J., Tang, J., & Guo, F. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac008 · Cited by 17

Reconstructing gene regulatory networks of biological function using differential equations of multilayer perceptrons

Mao, G., Zeng, R., Peng, J., Zuo, K., Pang, Z., & Liu, J. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-05055-5 · Cited by 17

Graph attention network with convolutional layer for predicting gene regulations from single-cell ribonucleic acid sequence data

Liu, J., Zhou, S., Ma, J., Zang, M., Liu, C., Liu, T., & Wang, Q. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108938 · Cited by 16

Exploring interspecific interaction variability in microbiota: A review

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Deep Learning in Gene Regulatory Network Inference: A Survey

Dong, J., Li, J., & Wang, F. (2024) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2024.3442536 · Cited by 16

Transiently Increased Coordination in Gene Regulation During Cell Phenotypic Transitions

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Theoretical and computational tools to model multistable gene regulatory networks

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Gene Regulatory Network Inference Using Convolutional Neural Networks from scRNA-seq Data

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Quantifying Landscape‐Flux via Single‐Cell Transcriptomics Uncovers the Underlying Mechanism of Cell Cycle

Zhu, L., & Wang, J. (2024) · Advanced Science · doi:10.1002/advs.202308879 · Cited by 13

Inferring gene regulatory networks from time-series scRNA-seq data via GRANGER causal recurrent autoencoders

Chen, L., Dautle, M., Gao, R., Zhang, S., & Chen, Y. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf089 · Cited by 16

Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data

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Computational approaches to understand transcription regulation in development

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Learning cell-specific networks from dynamics and geometry of single cells

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Advancing single-cell omics and cell-based therapeutics with quantum computing

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Network Modeling and Control of Dynamic Disease Pathways, Review and Perspectives

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Modeling single cell trajectory using forward-backward stochastic differential equations

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Inferring gene regulatory networks from single-cell RNA-seq temporal snapshot data requires higher-order moments

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Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data

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From sampling to simulating: Single-cell multiomics in systems pathophysiological modeling

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Evaluating Gene Regulatory Network Activity From Dynamic Expression Data by Regularized Constraint Programming

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EnsInfer: a simple ensemble approach to network inference outperforms any single method

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DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations

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Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods

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Dynamic gene regulatory network inference from single-cell data using optimal transport

Lamoline, F., Haasler, I., Karlsson, J., Gonçalves, J. M., & Aalto, A. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf394 · Cited by 8

XGRN: Reconstruction of Biological Networks Based on Boosted Trees Regression

Dimitrakopoulos, G. Ν. (2021) · Computation · doi:10.3390/computation9040048 · Cited by 7

Diffusion-based generation of gene regulatory networks from scRNA-seq data with DigNetPreprint

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Continuous lifelong learning for modeling of gene regulation from single cell multiome data by leveraging atlas-scale external dataPreprint

Yuan, Q., & Duren, Z. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.01.551575 · Cited by 6

Joint Gene Network Construction by Single-Cell RNA Sequencing Data

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COFFEE: consensus single cell-type specific inference for gene regulatory networks

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Prioritizing Autism Risk Genes Using Personalized Graphical Models Estimated From Single-Cell RNA-seq Data

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Interpretable single-cell transcription factor prediction based on deep learning with attention mechanism

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NG-SEM: an effective non-Gaussian structural equation modeling framework for gene regulatory network inference from single-cell RNA-seq data

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Linear system identification from ensemble snapshot observations

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Five Years of Gene Networks Modeling in Single-cell RNA-sequencing Studies: Current Approaches and Outstanding Challenges

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A survey of the methodological process of modeling, inference, and evaluation of gene regulatory networks using scRNA-Seq data

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Linear system identifiability from single-cell data

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Inference of gene coexpression networks from single-cell transcriptome data based on variance decomposition analysis

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Fusion prior gene network for high reliable single-cell gene regulatory network inference

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MKG: a mutual information based method to infer single cell gene regulatory network

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Integrated Pipelines for Inferring Gene Regulatory Networks from Single-Cell Data

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Transiently increased intercommunity regulation characterizes concerted cell phenotypic transitionPreprint

Wang, W., Ni, K., Poe, D., & Xing, J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.21.461257 · Cited by 3

Context-dependent gene regulatory network reveals regulation dynamics and cell trajectories using unspliced transcripts

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Reconstruction of gene regulatory networks from single cell transcriptomic data

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Integrating Machine Learning and Biological Context for Single-Cell Gene Regulatory Network Inference

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OneSC: a computational platform for recapitulating cell state transitions

Peng, D., & Cahan, P. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae703 · Cited by 1

Kolmogorov-Arnold Network for Gene Regulatory Network Inference

Tong, T. P., Wang, A., Panagopoulos, G., & Pang, J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-01436-8_12 · Cited by 1

Attention-Guided Probabilistic Diffusion Model for Generating Cell-Type-Specific Gene Regulatory Networks from Gene Expression Profiles

Xu, S., Yu, N., Zhang, D., & Wang, C. (2025) · Genes · doi:10.3390/genes16111255 · Cited by 1

DeepCE: a deep learning framework for correlation-enhanced gene regulatory network inference in single-cell RNA sequencing data

Wu, Q., Dai, X., Lou, S., Wu, S., & Tian, T. (2026) · Bioinformatics Advances · doi:10.1093/bioadv/vbag033 · Cited by 1

Multiscale learning of gene network-driven phenotypic dynamics of single cells

Zhang, D., Li, J., Nie, Q. H., & (493308), X. S. (2026) · Molecular Systems Biology · doi:10.1038/s44320-026-00220-x · Cited by 2

Identification of condition-specific regulatory mechanisms in normal and cancerous human lung tissue

Hang, Y., Burns, J., Shealy, B. T., Pauly, R., Ficklin, S. P., & Feltus, F. A. (2022) · BMC Genomics · doi:10.1186/s12864-022-08591-9 · Cited by 1

Distinct characteristics of correlation analysis at the single-cell and the population level

Wu, G., & Li, Y. (2022) · Statistical Applications in Genetics and Molecular Biology · doi:10.1515/sagmb-2022-0015 · Cited by 1

Gene Regulatory Network Reconstruction Using Single-Cell RNA-Sequencing

Koumadorakis, D. E., Dimitrakopoulos, G. Ν., Krokidis, M. G., & Vrahatis, A. G. (2023) · Springer eBooks · doi:10.1007/978-3-319-75922-7_18 · Cited by 1

A flexible gene regulatory network reconstruction method based on autoencoder and graph attention network

Zheng, R., Zeng, Y., Zeng, W., & Li, M. (2023) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm58861.2023.10385420 · Cited by 1

scSGL: Signed Graph Learning for Single-Cell Gene Regulatory Network InferencePreprint

Karaaslanli, A., Saha, S., Aviyente, S., & Maiti, T. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.08.451697 · Cited by 1

An Adaptive Stacking Ensemble Approach to Network Inference Outperforms Any Single MethodPreprint

Shen, B., Coruzzi, G. M., & Shasha, D. E. (2022) · Research Square · doi:10.21203/rs.3.rs-1456294/v1 · Cited by 1

scmTE: multivariate transfer entropy builds interpretable compact gene regulatory networks by reducing false predictionsPreprint

Weng, G., Kim, J., Natarajan, K. N., & Won, K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.08.515579 · Cited by 1

Ordinary differential equations to construct invertible generative models of cell type and tissue-specific regulatory networksPreprint

Niktab, E., Atkinson, P. H., Walterfang, M., Winship, I., Sturley, S. L., & Munkacsi, A. B. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.18.540731 · Cited by 1

Direct Reconstruction of Gene Regulatory Networks underlying Cellular state Transitions without Pseudo-time InferencePreprint

Wan, R., Zhang, Y., Peng, Y., Tian, F., Gao, G., Tang, F., Xie, X. S., Jia, J., & Ge, H. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.12.443928

Systems biology in disease modeling and control, analysis and perspectivesPreprint

Yue, R., & Dutta, A. (2021) · Research Square · doi:10.21203/rs.3.rs-578017/v1

The current state of methods for gene regulatory networks reconstruction

Liakh, I. (2021) · Scientific Papers (Ukrainian Academy of Printing) · doi:10.32403/1998-6912-2021-2-63-97-111

Gene Regulatory Network Reconstruction Using Single-Cell RNA-Sequencing

Koumadorakis, D. E., Dimitrakopoulos, G. Ν., Krokidis, M. G., & Vrahatis, A. G. (2022) · Springer eBooks · doi:10.1007/978-3-319-75479-6_18-1

Continuing Education Network Data Center Model Based on Fractional Differential Mathematical Equations

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Graph Neural Networks to Identify Genetic Modifiers of Rare Complex Inheritable Diseases

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