ArticleGenome biology2022
NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 61 citations in OpenAlex.
- Joint inference of paired dynamical gene regulatory networks reveals distinct cell-state landscapes of neutrophil reprogramming.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking methods for inferring single-cell transcription factor activity using large-scale perturbation sequencing data.Briefings in bioinformatics · 2026Article
- Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.Molecular systems biology · 2026Article
- Single-cell and spatial transcriptomics reveal TNF-α promotes glioblastoma proliferation and migration via CP-mediated KLF10 upregulation.Functional & integrative genomics · 2026Article
- sRACIPE 2.0: a systems biology circuit modeling toolkit for random circuit perturbation.Bioinformatics (Oxford, England) · 2026Article
- Building dynamical models of multi-step state transitions from single cell gene expression trajectories.bioRxiv : the preprint server for biology · 2025Article
- Reconstructing gene network structure and dynamics from single cell data.Bioinformatics (Oxford, England) · 2025Article
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- Signaling and transcriptional dynamics underlying early adaptation to oncogenic BRAF inhibition.Cell systems · 2025Article
- Multi-omic analyses reveal aberrant DNA methylation patterns and the associated biomarkers of nasopharyngeal carcinoma and its cancer stem cells.Scientific reports · 2025Article
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- Global transcription machinery engineering in Yarrowia lipolytica.FEMS yeast research · 2025Review
- Neutrophil extracellular traps: a novel contributor to vascular calcification in chronic kidney disease.Frontiers in immunology · 2025Article
- Predicting TF-Target Gene Association Using a Heterogeneous Network and Enhanced Negative Sampling.Bioinformatics and biology insights · 2025Article
- Endothelial Dysfunction in the Tubule Area Accelerates the Progression of Early Diabetic Kidney Disease.Physiological research · 2024Article
- OneSC: a computational platform for recapitulating cell state transitions.Bioinformatics (Oxford, England) · 2024Article
- Network modeling links kidney developmental programs and the cancer type-specificity of VHL mutations.NPJ systems biology and applications · 2024Article
- An Interplay between Transcription Factors and Recombinant Protein Synthesis inInternational journal of molecular sciences · 2024Article
- Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets.Briefings in bioinformatics · 2024Review
- Computational Reconstruction of the Transcription Factor Regulatory Network Induced by Auxin inPlants (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 1 country.
Funding
Abstract
A major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators' activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-β-induced epithelial-mesenchymal transition and macrophage polarization.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.