ArticleGenome biology2023
CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms.
Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed.
- EPInformer: scalable and integrative prediction of gene expression from promoter-enhancer sequences with multimodal epigenomic profiles.Nature communications · 2026Article
- EpiExpr: Predicting gene expression using epigenetic data and chromatin interactions.bioRxiv : the preprint server for biology · 2026Article
- A scalable computational framework for predicting gene expression from candidateGenome research · 2026Article
- Article
- Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Foundation model for comprehensive transcriptional regulation analysis.National science review · 2024Article
- Article
- CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms.Genome biology · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Linking cis-regulatory sequences to target genes has been a long-standing challenge. In this study, we introduce CREaTor, an attention-based deep neural network designed to model cis-regulatory patterns for genomic elements up to 2 Mb from target genes. Coupled with a training strategy that predicts gene expression from flanking candidate cis-regulatory elements (cCREs), CREaTor can model cell type-specific cis-regulatory patterns in new cell types without prior knowledge of cCRE-gene interactions or additional training. The zero-shot modeling capability, combined with the use of only RNA-seq and ChIP-seq data, allows for the ready generalization of CREaTor to a broad range of cell types.
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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 Socratic graph.