ArticleBioinformatics (Oxford, England)2018
Predicting CTCF-mediated chromatin loops using CTCF-MP.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 64 citations in OpenAlex.
- GraphChIAr: genome-wide super-resolution reconstruction of protein-mediated remote chromatin interactions by augmenting hi-C interaction maps with multiple ChIP-seq profiles.Briefings in bioinformatics · 2026Article
- TF-loop: deciphering the transcription factor regulatory language for CTCF-mediated chromatin loop based on BERT.Briefings in bioinformatics · 2026Article
- UniChrom: a universal deep learning architecture for cross-scale chromatin interaction prediction.BMC genomics · 2026Article
- CLAMP: predicting specific protein-mediated chromatin loops in diverse species with a chromatin accessibility language model.Genome biology · 2026Article
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- EPIFBMC: A New Model for Enhancer-Promoter Interaction Prediction.International journal of molecular sciences · 2025Article
- Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Gaining insights into Alzheimer's disease by predicting chromatin spatial organization.Bioinformatics advances · 2025Article
- Polymer Physics Models Reveal Structural Folding Features of Single-Molecule Gene Chromatin Conformations.International journal of molecular sciences · 2024Article
- Article
- Computational methods for analysing multiscale 3D genome organization.Nature reviews. Genetics · 2024Review
- DeepCBS: shedding light on the impact of mutations occurring at CTCF binding sites.Frontiers in genetics · 2024Article
- CD-Loop: a chromatin loop detection method based on the diffusion model.Frontiers in genetics · 2024Article
- Inferring CTCF-binding patterns and anchored loops across human tissues and cell types.Patterns (New York, N.Y.) · 2023Article
- CapsNetYY1: identifying YY1-mediated chromatin loops based on a capsule network architecture.BMC genomics · 2023Article
- DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks.PLoS computational biology · 2023Article
- Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation.PLoS computational biology · 2023Article
- Benefiting from the intrinsic role of epigenetics to predict patterns of CTCF binding.Computational and structural biotechnology journal · 2023Article
- Article
- Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine.Biochimica et biophysica acta. Reviews on cancer · 2021Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Motivation: The three dimensional organization of chromosomes within the cell nucleus is highly regulated. It is known that CCCTC-binding factor (CTCF) is an important architectural protein to mediate long-range chromatin loops. Recent studies have shown that the majority of CTCF binding motif pairs at chromatin loop anchor regions are in convergent orientation. However, it remains unknown whether the genomic context at the sequence level can determine if a convergent CTCF motif pair is able to form a chromatin loop. Results: In this article, we directly ask whether and what sequence-based features (other than the motif itself) may be important to establish CTCF-mediated chromatin loops. We found that motif conservation measured by 'branch-of-origin' that accounts for motif turn-over in evolution is an important feature. We developed a new machine learning algorithm called CTCF-MP based on word2vec to demonstrate that sequence-based features alone have the capability to predict if a pair of convergent CTCF motifs would form a loop. Together with functional genomic signals from CTCF ChIP-seq and DNase-seq, CTCF-MP is able to make highly accurate predictions on whether a convergent CTCF motif pair would form a loop in a single cell type and also across different cell types. Our work represents an important step further to understand the sequence determinants that may guide the formation of complex chromatin architectures. Availability and implementation: The source code of CTCF-MP can be accessed at: https://github.com/ma-compbio/CTCF-MP. 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.