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Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information

Transcription factors play key roles in cell-fate decisions by regulating 3D genome conformation and gene expression. The traditional view is that methylation of DNA hinders transcription factors binding to them, but recent research has shown that many transcription factors prefer to bind to methyla...

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Autores principales: Liu, Meng-Lu, Su, Wei, Wang, Jia-Shu, Yang, Yu-He, Yang, Hui, Lin, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691157/
https://www.ncbi.nlm.nih.gov/pubmed/33294291
http://dx.doi.org/10.1016/j.omtn.2020.07.035
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author Liu, Meng-Lu
Su, Wei
Wang, Jia-Shu
Yang, Yu-He
Yang, Hui
Lin, Hao
author_facet Liu, Meng-Lu
Su, Wei
Wang, Jia-Shu
Yang, Yu-He
Yang, Hui
Lin, Hao
author_sort Liu, Meng-Lu
collection PubMed
description Transcription factors play key roles in cell-fate decisions by regulating 3D genome conformation and gene expression. The traditional view is that methylation of DNA hinders transcription factors binding to them, but recent research has shown that many transcription factors prefer to bind to methylated DNA. Therefore, identifying such transcription factors and understanding their functions is a stepping-stone for studying methylation-mediated biological processes. In this paper, a two-step discriminated method was proposed to recognize transcription factors and their preference for methylated DNA based only on sequences information. In the first step, the proposed model was used to discriminate transcription factors from non-transcription factors. The areas under the curve (AUCs) are 0.9183 and 0.9116, respectively, for the 5-fold cross-validation test and independent dataset test. Subsequently, for the classification of transcription factors that prefer methylated DNA and transcription factors that prefer non-methylated DNA, our model could produce the AUCs of 0.7744 and 0.7356, respectively, for the 5-fold cross-validation test and independent dataset test. Based on the proposed model, a user-friendly web server called TFPred was built, which can be freely accessed at http://lin-group.cn/server/TFPred/.
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spelling pubmed-76911572020-12-07 Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information Liu, Meng-Lu Su, Wei Wang, Jia-Shu Yang, Yu-He Yang, Hui Lin, Hao Mol Ther Nucleic Acids Original Article Transcription factors play key roles in cell-fate decisions by regulating 3D genome conformation and gene expression. The traditional view is that methylation of DNA hinders transcription factors binding to them, but recent research has shown that many transcription factors prefer to bind to methylated DNA. Therefore, identifying such transcription factors and understanding their functions is a stepping-stone for studying methylation-mediated biological processes. In this paper, a two-step discriminated method was proposed to recognize transcription factors and their preference for methylated DNA based only on sequences information. In the first step, the proposed model was used to discriminate transcription factors from non-transcription factors. The areas under the curve (AUCs) are 0.9183 and 0.9116, respectively, for the 5-fold cross-validation test and independent dataset test. Subsequently, for the classification of transcription factors that prefer methylated DNA and transcription factors that prefer non-methylated DNA, our model could produce the AUCs of 0.7744 and 0.7356, respectively, for the 5-fold cross-validation test and independent dataset test. Based on the proposed model, a user-friendly web server called TFPred was built, which can be freely accessed at http://lin-group.cn/server/TFPred/. American Society of Gene & Cell Therapy 2020-07-31 /pmc/articles/PMC7691157/ /pubmed/33294291 http://dx.doi.org/10.1016/j.omtn.2020.07.035 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Liu, Meng-Lu
Su, Wei
Wang, Jia-Shu
Yang, Yu-He
Yang, Hui
Lin, Hao
Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
title Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
title_full Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
title_fullStr Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
title_full_unstemmed Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
title_short Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
title_sort predicting preference of transcription factors for methylated dna using sequence information
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691157/
https://www.ncbi.nlm.nih.gov/pubmed/33294291
http://dx.doi.org/10.1016/j.omtn.2020.07.035
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