Evidence map›Paper›PMID 38189539›Full record

ArticleBriefings in bioinformatics2023

CEMIG: prediction of the cis-regulatory motif using the de Bruijn graph from ATAC-seq.

Yizhong Wang, Yang Li, Cankun Wang, Chan-Wang Jerry Lio, Qin Ma, Bingqiang Liu

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Yizhong WangSchool of Mathematics, Shandong University, Jinan, 250100, China.
Yang LiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
Cankun WangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
Chan-Wang Jerry LioDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
Qin MaDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
Bingqiang LiuSchool of Mathematics, Shandong University, Jinan, 250100, China.

Funding

Molecular Mechanism of TET-mediated Gene RegulationR35GM151110 · NIGMS · OHIO STATE UNIVERSITY · PI Jerry Chan-Wang Lio · 2023 to 2026
$1.5M
National Key Research and Development Program of China 2020YFA0712400National Nature Science Foundation of China 62272270NIGMS NIH HHS R35 GM151110Shandong University Multidisciplinary Research and Innovation Team of Young Scholars 2020QNQT017
6 · The paper itself

Abstract

Sequence motif discovery algorithms enhance the identification of novel deoxyribonucleic acid sequences with pivotal biological significance, especially transcription factor (TF)-binding motifs. The advent of assay for transposase-accessible chromatin using sequencing (ATAC-seq) has broadened the toolkit for motif characterization. Nonetheless, prevailing computational approaches have focused on delineating TF-binding footprints, with motif discovery receiving less attention. Herein, we present Cis rEgulatory Motif Influence using de Bruijn Graph (CEMIG), an algorithm leveraging de Bruijn and Hamming distance graph paradigms to predict and map motif sites. Assessment on 129 ATAC-seq datasets from the Cistrome Data Browser demonstrates CEMIG's exceptional performance, surpassing three established methodologies on four evaluative metrics. CEMIG accurately identifies both cell-type-specific and common TF motifs within GM12878 and K562 cell lines, demonstrating its comparative genomic capabilities in the identification of evolutionary conservation and cell-type specificity. In-depth transcriptional and functional genomic studies have validated the functional relevance of CEMIG-identified motifs across various cell types. CEMIG is available at https://github.com/OSU-BMBL/CEMIG, developed in C++ to ensure cross-platform compatibility with Linux, macOS and Windows operating systems.

Indexed as

AlgorithmsChromatin Immunoprecipitation SequencingBiological EvolutionCell Linealgorithmschromatin accessibilitycluster analysisgraph theorymotif finding

Identifiers

PMID38189539
PMCPMC10772951

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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.