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Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information

Menglu Liu, Wei Su, Jia-Shu Wang, Yuhe R. Yang, Hui Yang, Hao Lin

2020Molecular Therapy — Nucleic Acids32 citationsDOIOpen Access PDF

Abstract

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/.

Topics & Concepts

Transcription (linguistics)PreferenceComputational biologyDNASequence (biology)GeneticsTranscription factorDNA methylationDNA sequencingBiologyGeneMathematicsGene expressionStatisticsLinguisticsPhilosophyMachine Learning in BioinformaticsGenomics and Chromatin DynamicsGenomics and Phylogenetic Studies
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