ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
SEE: A Method for Predicting the Dynamics of Chromatin Conformation Based on Single-Cell Gene Expression.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Nuclear mechanotransduction: tools for mechanical perturbation and chromatin characterization.Nucleus (Austin, Tex.) · 2026Review
- scWeave: A deep learning model that bidirectionally translates between gene expression and chromatin structure at single-cell resolution.bioRxiv : the preprint server for biology · 2026Article
- 3D Genome Architecture in Stem Cell Lineage Commitment: from Structural Organization to Precision Regulation.Advanced genetics (Hoboken, N.J.) · 2025Review
- SEE: A Method for Predicting the Dynamics of Chromatin Conformation Based on Single-Cell Gene Expression.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Topologically associating domains of chromatin on single-cell Hi-C data: a survey of bioinformatic tools and applications in the light of artificial intelligence.Frontiers in genetics · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The dynamics of chromatin conformation involve continuous and reversible changes within the nucleus of a cell, which participate in regulating processes such as gene expression, DNA replication, and damage repair. Here, SEE is introduced, an artificial intelligence (AI) method that utilizes autoencoder and transformer techniques to analyze chromatin dynamics using single-cell RNA sequencing data and a limited number of single-cell Hi-C maps. SEE is employed to investigate chromatin dynamics across different scales, enabling the detection of (i) rearrangements in topologically associating domains (TADs), and (ii) oscillations in chromatin interactions at gene loci. Additionally, SEE facilitates the interpretation of disease-associated single-nucleotide polymorphisms (SNPs) by leveraging the dynamic features of chromatin conformation. Overall, SEE offers a single-cell, high-resolution approach to analyzing chromatin dynamics in both developmental and disease contexts.
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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.