Evidence map›Paper›PMID 41607593›Full record

ArticleFrontiers in genetics2026

Bream: an open-source deep learning framework for simultaneous base calling and DNA methylation detection on novel nanopore sequencing platforms.

Hui-Cong Yao, Bo Wu, Chen-Liang Ye, Xin Bai, He-Xu Chen, Geng Hu, Chuan-Le Xiao

Abstract read
In one paragraph

Article in Frontiers in genetics, 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. Review
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

7 authors.

Hui-Cong YaoSchool of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China.
Bo WuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Chen-Liang YeState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Xin BaiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
He-Xu ChenSchool of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China.
Geng HuBioinformatics and Product Development Department, Qitan Technology (Beijing) Co., Ltd, Beijing, China.
Chuan-Le XiaoState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanopore sequencing enables the simultaneous detection of genetic sequences and DNA modifications, yet the development of accurate, open-source computational models for these tasks, particularly for non-ONT platforms, remains challenging. To address this, we developed Bream, an open-source deep learning framework that integrates a convolutional neural network with a reverse long short-term memory network for base calling and a bidirectional LSTM with an attention mechanism for methylation detection. We trained and evaluated Bream on datasets from

Indexed as

base callingbreamdeep learningmethylation detectionqitan

Identifiers

PMID41607593
PMCPMC12844561

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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.