ArticleNPJ systems biology and applications2024
Flexible modeling of regulatory networks improves transcription factor activity estimation.
Article in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- A transcription factor regulatory atlas for activity inference and perturbation prediction.Nucleic acids research · 2026Article
- Benchmarking methods for inferring single-cell transcription factor activity using large-scale perturbation sequencing data.Briefings in bioinformatics · 2026Article
- Disentangling factors affecting bacterial transcriptional regulatory network inference.iScience · 2026Article
- Large-scale, interpretable gene regulatory network inference through biologically informed matrix factorization.bioRxiv : the preprint server for biology · 2026Article
- Multimodal bioinformatic analyses of genome-scale expression beyond gene-centric differential expression.Briefings in bioinformatics · 2026Review
- A stem cell knockout village reveals lineage rewiring and a non-canonical islet cell fate in monogenic diabetes.bioRxiv : the preprint server for biology · 2025Article
- Multi-omics protein signaling networks identify sex-specific therapeutic candidates in lung adenocarcinoma.Biology of sex differences · 2025Article
- Single-cell RNA sequencing technology was employed to construct a risk prediction model for genes associated with pyroptosis and ferroptosis in lung adenocarcinoma.Respiratory research · 2025Article
- Identifying Sex Differences in Lung Adenocarcinoma Using Multi-Omics Integrative Protein Signaling Networks.bioRxiv : the preprint server for biology · 2025Article
- Reproducible processing of TCGA regulatory networks.GigaScience · 2025Article
- In silico screening system based on a transcription factors regulatory network only using transcriptomic data.PloS one · 2025Article
- Shared transcriptional regulators and network rewiring identify therapeutic targets linking type 2 diabetes mellitus and hypertension.Frontiers in molecular biosciences · 2025Article
- Selective loss of Y chromosomes in lung adenocarcinoma modulates the tumor immune environment through cancer/testis antigens.bioRxiv : the preprint server for biology · 2024Article
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2 authors.
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Abstract
Transcriptional regulation plays a crucial role in determining cell fate and disease, yet inferring the key regulators from gene expression data remains a significant challenge. Existing methods for estimating transcription factor (TF) activity often rely on static TF-gene interaction databases and cannot adapt to changes in regulatory mechanisms across different cell types and disease conditions. Here, we present a new algorithm - Transcriptional Inference using Gene Expression and Regulatory data (TIGER) - that overcomes these limitations by flexibly modeling activation and inhibition events, up-weighting essential edges, shrinking irrelevant edges towards zero through a sparse Bayesian prior, and simultaneously estimating both TF activity levels and changes in the underlying regulatory network. When applied to yeast and cancer TF knock-out datasets, TIGER outperforms comparable methods in terms of prediction accuracy. Moreover, our application of TIGER to tissue- and cell-type-specific RNA-seq data demonstrates its ability to uncover differences in regulatory mechanisms. Collectively, our findings highlight the utility of modeling context-specific regulation when inferring transcription factor activities.
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