ArticleScientific reports2016
PETModule: a motif module based approach for enhancer target gene prediction.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- CRM-TI: an enhanced pipeline for computationally assigning the target genes of cis-regulatory modules by considering comprehensive long-range regulation mechanisms.BioData mining · 2026Article
- Prediction of target genes and functional types of cis-regulatory modules in the human genome reveals their distinct properties.BMC biology · 2025Article
- Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Article
- A computational modeling of pri-miRNA expression.PloS one · 2024Article
- Integrative approaches based on genomic techniques in the functional studies on enhancers.Briefings in bioinformatics · 2023Review
- A systematic study of HIF1A cofactors in hypoxic cancer cells.Scientific reports · 2022Article
- A systematic evaluation of the computational tools for ligand-receptor-based cell-cell interaction inference.Briefings in functional genomics · 2022Article
- A revisit to universal single-copy genes in bacterial genomes.Scientific reports · 2022Article
- A deep learning method for miRNA/isomiR target detection.Scientific reports · 2022Article
- A systematic study of motif pairs that may facilitate enhancer-promoter interactions.Journal of integrative bioinformatics · 2022Article
- Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory interactions.Nucleic acids research · 2021Article
- Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.Briefings in bioinformatics · 2021Article
- Interpretation of deep learning in genomics and epigenomics.Briefings in bioinformatics · 2021Review
- An intriguing characteristic of enhancer-promoter interactions.BMC genomics · 2021Article
- Shared distal regulatory regions may contribute to the coordinated expression of human ribosomal protein genes.Genomics · 2020Article
- A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods.Genome biology · 2020Article
- Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction.Computational and structural biotechnology journal · 2020Review
- 7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs.BMC genomics · 2019Article
- EPIP: a novel approach for condition-specific enhancer-promoter interaction prediction.Bioinformatics (Oxford, England) · 2019Article
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3 authors.
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Abstract
The identification of enhancer-target gene (ETG) pairs is vital for the understanding of gene transcriptional regulation. Experimental approaches such as Hi-C have generated valuable resources of ETG pairs. Several computational methods have also been developed to successfully predict ETG interactions. Despite these progresses, high-throughput experimental approaches are still costly and existing computational approaches are still suboptimal and not easy to apply. Here we developed a motif module based approach called PETModule that predicts ETG pairs. Tested on eight human cell types and two mouse cell types, we showed that a large number of our predictions were supported by Hi-C and/or ChIA-PET experiments. Compared with two recently developed approaches for ETG pair prediction, we shown that PETModule had a much better recall, a similar or better F1 score, and a larger area under the receiver operating characteristic curve. The PETModule tool is freely available at http://hulab.ucf.edu/research/projects/PETModule/.
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