ArticleiMeta2025
RepliChrom: Interpretable machine learning predicts cancer-associated enhancer-promoter interactions using DNA replication timing.
Article in iMeta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The trial behind it
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Who cites it
16 citing papers in PubMed.
- Comprehensive evaluation of structural variation detection for germline and somatic analysis with long-read sequencing data.Briefings in bioinformatics · 2026Article
- iBitter-HF: A Method for Bitter Peptide Sequence Identification Based on Hybrid Feature Embedding.Foods (Basel, Switzerland) · 2026Article
- HMA-GCA: hybrid manifold augmentation and gated cross-attention for circRNA-miRNA interaction prediction.Bioinformatics (Oxford, England) · 2026Article
- MVFAN-Kcr: A Multi-View Feature Fusion and Attention-Based Network for Lysine Crotonylation Site Identification.Interdisciplinary sciences, computational life sciences · 2026Article
- CataCon: a contrastive graph representation learning framework for catalyst prediction.Journal of cheminformatics · 2026Article
- MsgaBpred: A B-cell epitope predictor integrating AlphaFold3-predicted structures with multi-scale GCNs and pre-trained language model ESM-C.PLoS computational biology · 2026Article
- TF-loop: deciphering the transcription factor regulatory language for CTCF-mediated chromatin loop based on BERT.Briefings in bioinformatics · 2026Article
- FKSUDDAPre: A drug-disease association prediction framework based on F-TEST feature selection and AMDKSU resampling with interpretability analysis.PLoS computational biology · 2026Article
- Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics.Briefings in bioinformatics · 2026Article
- Semantic-enhanced heterogeneous graph learning for identifying ncRNAs associated with drug resistance.Bioinformatics (Oxford, England) · 2026Article
- ProjFusNet: deep neural network for peptide precursor prediction using projection-fused protein language model and structural features.Journal of cheminformatics · 2025Article
- HyperACP: A cutting-edge hybrid framework for anticancer peptide classification via scalable feature extraction and adaptive neighbor-based synthesis.PLoS computational biology · 2025Article
- A Multi-Omics Integration Framework with Automated Machine Learning Identifies Peripheral Immune-Coagulation Biomarkers for Schizophrenia Risk Stratification.International journal of molecular sciences · 2025Article
- Article
- NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides.BMC biology · 2025Article
- Machine Learning-based Diagnostic Potential of Bipolar Disorder Using Gut Microbiota Signatures.IET systems biologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RepliChrom is an interpretable machine learning model that predicts enhancer-promoter interactions using DNA replication timing across multiple cell types. By integrating replication timing with chromatin interaction data from multiple experimental platforms, it accurately distinguishes true interactions and reveals promoter-region signals as key regulatory drivers. Importantly, the RepliChrom uncovers cancer-specific chromatin patterns in leukemia, offering mechanistic insights into how replication timing shapes long-range gene regulation in both normal and diseased genomes.
Identifiers
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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.