ArticleBioinformatics (Oxford, England)2019
TEPIC 2-an extended framework for transcription factor binding prediction and integrative epigenomic analysis.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Improved linking of motifs to their TFs using domain information.Bioinformatics (Oxford, England) · 2020Pooled it
- Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.Genome biology · 2026Article
- Multimodal bioinformatic analyses of genome-scale expression beyond gene-centric differential expression.Briefings in bioinformatics · 2026Review
- WSHNN: A Weakly Supervised Hybrid Neural Network for the Identification of DNA-protein Binding Sites.Current computer-aided drug design · 2025Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Multiomics analysis identifies novel facilitators of human dopaminergic neuron differentiation.EMBO reports · 2024Article
- Widespread effects of DNA methylation and intra-motif dependencies revealed by novel transcription factor binding models.Nucleic acids research · 2023Article
- CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes.Human genomics · 2023Article
- Alterations in the hepatocyte epigenetic landscape in steatosis.Epigenetics & chromatin · 2023Article
- Computational approaches to understand transcription regulation in development.Biochemical Society transactions · 2023Review
- The adapted Activity-By-Contact model for enhancer-gene assignment and its application to single-cell data.Bioinformatics (Oxford, England) · 2023Article
- TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors.GigaScience · 2022Article
- Increased chromatin accessibility facilitates intron retention in specific cell differentiation states.Nucleic acids research · 2022Article
- Nuclear receptor activation shapes spatial genome organization essential for gene expression control: lessons learned from the vitamin D receptor.Nucleic acids research · 2022Article
- Constructing gene regulatory networks using epigenetic data.NPJ systems biology and applications · 2021Article
- Integrative analysis of epigenetics data identifies gene-specific regulatory elements.Nucleic acids research · 2021Article
- Systems biology for crop improvement.The plant genome · 2021Review
- A hierarchical regulatory network analysis of the vitamin D induced transcriptome reveals novel regulators and complete VDR dependency in monocytes.Scientific reports · 2021Article
- ATG5 and ATG7 Expression Levels Are Reduced in Cutaneous Melanoma and Regulated by NRF1.Frontiers in oncology · 2021Article
- GeneTrail: A Framework for the Analysis of High-Throughput Profiles.Frontiers in molecular biosciences · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
summaryPrediction of transcription factor (TF) binding from epigenetics data and integrative analysis thereof are challenging. Here, we present TEPIC 2 a framework allowing for fast, accurate and versatile prediction, and analysis of TF binding from epigenetics data: it supports 30 species with binding motifs, computes TF gene and scores up to two orders of magnitude faster than before due to improved implementation, and offers easy-to-use machine learning pipelines for integrated analysis of TF binding predictions with gene expression data allowing the identification of important TFs. AVAILABILITY AND IMPLEMENTATION: TEPIC is implemented in C++, R, and Python. It is freely available at https://github.com/SchulzLab/TEPIC and can be used on Linux based systems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.