Identifying Transcription Factors That Prefer Binding to Methylated DNA Using Reduced <i>G</i>-Gap Dipeptide Composition-Reference-Cited by-同舟云学术

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Identifying Transcription Factors That Prefer Binding to Methylated DNA Using Reduced G-Gap Dipeptide Composition

Published:2022-08-30 Issue:36 Volume:7 Page:32322-32330
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Nguyen Quang H.¹,Tran Hoang V.¹^ORCID,Nguyen Binh P.²^ORCID,Do Trang T. T.³^ORCID

Affiliation:

1. School of Information and Communication Technology, Hanoi University of Science and Technology, 1 Dai Co Viet, Hanoi 100000, Vietnam

2. School of Mathematics and Statistics, Victoria University of Wellington, Kelburn Parade, Wellington 6140, New Zealand

3. School of Innovation, Design and Technology, Wellington Institute of Technology, 21 Kensington Avenue, Lower Hutt 5012, New Zealand

Funder

Qu? Ð?i m?i sáng t?o Vingroup

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c03696

Reference37 articles.

1. Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites

2. Mechanisms of Interplay between Transcription Factors and the 3D Genome

3. Cross-talk between Site-specific Transcription Factors and DNA Methylation States

4. Toward a Mechanistic Understanding of DNA Methylation Readout by Transcription Factors

5. Sensitivity of transcription factors to DNA methylation

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Uncovering the roles of DNA hemi-methylation in transcriptional regulation using MspJI-assisted hemi-methylation sequencing;Nucleic Acids Research;2024-01-23

2. 4mCPred-GSIMP: Predicting DNA N4-methylcytosine sites in the mouse genome with multi-Scale adaptive features extraction and fusion;Mathematical Biosciences and Engineering;2023

3. eMIC-AntiKP: Estimating minimum inhibitory concentrations of antibiotics towards Klebsiella pneumoniae using deep learning;Computational and Structural Biotechnology Journal;2023

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