ArticleScientific reports2018
dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.
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106 citing papers in PubMed.
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- The genetic signature of memory encoding along the human hippocampal axis.bioRxiv : the preprint server for biology · 2026Article
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- SpaTRACE: Spatiotemporal recurrent auto-encoder for reconstructing signaling and regulatory networks from spatiotemporal transcriptomics data.bioRxiv : the preprint server for biology · 2026Article
- Multimodal bioinformatic analyses of genome-scale expression beyond gene-centric differential expression.Briefings in bioinformatics · 2026Review
- Inference of Genetic Networks from Pseudo Time Series of Single-cell Gene Expression Data using Modified Random Forests.Bulletin of mathematical biology · 2026Article
- Clonal haematopoiesis of indeterminate potential and mortality in coronary artery disease.European heart journal · 2026Article
- Data driven network inference and longitudinal transcriptomics unveil dynamic regulation in Chronic Lymphocytic Leukaemia models.NPJ systems biology and applications · 2026Article
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- Bayesian Inference of Gene Regulatory Networks at Stochastic Steady State.bioRxiv : the preprint server for biology · 2026Article
- Temporal network analysis in systems biology: concepts, inference, and validation.Frontiers in bioinformatics · 2026Review
- HSTXGB: a hyperparameter self-tuning XGBoost method integrating pre- and post-processing for gene regulatory network inference.Frontiers in genetics · 2026Article
- From binding to networks: methods for identifying transcription factor targets in plant systems.Frontiers in plant science · 2026Review
- DANSE: a pipeline for dynamic modelling of time-series multi-omics data.BMC bioinformatics · 2025Article
- Gene regulatory network inference with popInfer reveals the dynamic regulation of hematopoietic stem cell quiescence.iScience · 2025Article
- Single-cell RNA sequencing reveals immune cell alterations in patients with allergic rhinitis treated with Peiyuan Tong-qiao decoction.Biochemistry and biophysics reports · 2025Article
- Multi-omic network inference from time-series data.NPJ systems biology and applications · 2025Article
46 more citing papers are in PubMed but not listed here.
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Abstract
The elucidation of gene regulatory networks is one of the major challenges of systems biology. Measurements about genes that are exploited by network inference methods are typically available either in the form of steady-state expression vectors or time series expression data. In our previous work, we proposed the GENIE3 method that exploits variable importance scores derived from Random forests to identify the regulators of each target gene. This method provided state-of-the-art performance on several benchmark datasets, but it could however not specifically be applied to time series expression data. We propose here an adaptation of the GENIE3 method, called dynamical GENIE3 (dynGENIE3), for handling both time series and steady-state expression data. The proposed method is evaluated extensively on the artificial DREAM4 benchmarks and on three real time series expression datasets. Although dynGENIE3 does not systematically yield the best performance on each and every network, it is competitive with diverse methods from the literature, while preserving the main advantages of GENIE3 in terms of scalability.
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