ArticleGenome research2018
Integrated analysis of motif activity and gene expression changes of transcription factors.
Article in Genome research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed, 77 citations in OpenAlex.
- E4BP4 safeguards brown fat mitochondria from obesity-induced fragmentation via ceramide repression.EMBO reports · 2026Article
- CroCoNet: a framework for the quantitative comparison of gene regulatory networks across species.Genome biology · 2026Article
- Article
- Motif-based models accurately predict cell type-specific distal regulatory elements.Nature communications · 2025Article
- Genetics-nutrition interactions control diurnal enhancer-promoter dynamics and liver lipid metabolism.Cell metabolism · 2025Article
- Epitranscriptomic Control of Drought Tolerance in Rice: The Role of RNA Methylation.Plants (Basel, Switzerland) · 2025Review
- Altering metabolism programs cell identity via NADThe EMBO journal · 2025Article
- Inhibition of triglyceride metabolism-associated enhancers alters lipid deposition during adipocyte differentiation.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025Article
- Transcriptome data are insufficient to control false discoveries in regulatory network inference.Cell systems · 2024Article
- Oncogenic enhancers prime quiescent metastatic cells to escape NK immune surveillance by eliciting transcriptional memory.Nature communications · 2024Article
- Single-cell multi-omics profiling of human preimplantation embryos identifies cytoskeletal defects during embryonic arrest.Nature cell biology · 2024Article
- Transcriptional programming of translation by BCL6 controls skeletal muscle proteostasis.Nature metabolism · 2024Article
- Predicting the impact of sequence motifs on gene regulation using single-cell data.Genome biology · 2023Article
- Hepatocyte SREBP signaling mediates clock communication within the liver.The Journal of clinical investigation · 2023Article
- Computational approaches to understand transcription regulation in development.Biochemical Society transactions · 2023Review
- Article
- xcore: an R package for inference of gene expression regulators.BMC bioinformatics · 2023Article
- Lipolysis regulates major transcriptional programs in brown adipocytes.Nature communications · 2022Article
- Characterization of regulatory transcriptional mechanisms in hepatocyte lipotoxicity.Scientific reports · 2022Article
- Using iRNA-seq analysis to predict gene expression regulatory level and activity in Zea mays tissues.G3 (Bethesda, Md.) · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability to predict transcription factors based on sequence information in regulatory elements is a key step in systems-level investigation of transcriptional regulation. Here, we have developed a novel tool, IMAGE, for precise prediction of causal transcription factors based on transcriptome profiling and genome-wide maps of enhancer activity. High precision is obtained by combining a near-complete database of position weight matrices (PWMs), generated by compiling public databases and systematic prediction of PWMs for uncharacterized transcription factors, with a state-of-the-art method for PWM scoring and a novel machine learning strategy, based on both enhancers and promoters, to predict the contribution of motifs to transcriptional activity. We applied IMAGE to published data obtained during 3T3-L1 adipocyte differentiation and showed that IMAGE predicts causal transcriptional regulators of this process with higher confidence than existing methods. Furthermore, we generated genome-wide maps of enhancer activity and transcripts during human mesenchymal stem cell commitment and adipocyte differentiation and used IMAGE to identify positive and negative transcriptional regulators of this process. Collectively, our results demonstrate that IMAGE is a powerful and precise method for prediction of regulators of gene expression.
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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.