Evidence map›Paper›PMID 41684299›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction.

Wenjie Huang, Li Tang, Matthew C Hill, Yonghao Zhang, Jun Xie, Min Li

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Wenjie HuangSchool of Computer Science and Engineering, Central South University, Changsha, China.
Li TangSchool of Computer Science and Engineering, Central South University, Changsha, China.
Matthew C HillCardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA.
Yonghao ZhangSchool of Computer Science and Engineering, Central South University, Changsha, China.
Jun XieSchool of Computer Science and Engineering, Central South University, Changsha, China.
Min LiSchool of Computer Science and Engineering, Central South University, Changsha, China.ORCID https://orcid.org/0000-0002-0188-1394

Funding

High-Performance Computing Center of Central South UniversityNational Natural Science Foundation of China 62225209National Natural Science Foundation of China 62320106009National Natural Science Foundation of China 62402529
6 · The paper itself

Abstract

Chromatin loops play a crucial role in gene regulation and cellular function, providing key insights into understanding the 3D structure of the genome and its impact on cellular homeostasis. Nanopore sequencing technology, with its advantages in simultaneously detecting sequences and methylation patterns, brings new opportunities for studying 3D genome structures. We introduce NanoLoop, the first algorithmic framework attempting to predict genome-wide chromatin interactions using Nanopore data. In experiments across four human lymphoblastoid cell lines, NanoLoop demonstrated excellent predictive performance and cross-cell line generalization capabilities. We also discovered four distinct methylation patterns at loop anchors that influence histone modification levels and determine various loop types. NanoLoop further predicted previously uncharacterized long-range chromatin loops, highlighting the potential link between DNA methylation and 3D genome organization and providing new insights into the complex regulatory relationships between epigenetic modifications and 3D genome organization.

Indexed as

ChromatinDeep LearningNanopore SequencingAlgorithmsDNA MethylationEpigenesis, GeneticHumansChromatinchromatin loopconvolutional neural networks (CNNs)DNA methylationepigenetic regulationnanopore sequencing

Identifiers

PMID41684299
PMCPMC13116353

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.