Article

Comparative Analysis of DNA Structural Parameters and the Corresponding Computational Tools to Differentiate Regulatory DNA Motifs and Promoters

2024-03-27

Abstract excerpt

<h4>ABSTRACT</h4> Analyzing and distinguishing functionally distinct DNA regions is crucial for various applications, including predicting DNA motifs and promoters, and exploring the mechanisms of gene expression regulation in disease conditions. Our understanding of mammalian promoters, particularly those associated with differentially expressed genes (DEGs), particularly remains limited. However, existing metho...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 92fba165-d7e5-5734-93ec-b36f179a04a0
DOI: 10.1101/2024.03.26.584893

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Comparative Analysis of DNA Structural Parameters and the Corresponding Computational Tools to Differentiate Regulatory DNA Motifs and PromotersDOI 10.1101/2024.03.26.584893Read

ShapeGTB: The role of local DNA shape in prioritization of functional variants in human promoters with machine learningSemantic proximity Read

TFBSshape: an expanded motif database for DNA shape features of transcription factor binding sites.Semantic proximity Read

Determination and inference of eukaryotic transcription factor sequence specificity.Semantic proximity Read

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factorsSemantic proximity Read

Codebook: sequence specificity and genomic binding of poorly-characterized human transcription factorsSemantic proximity Read

TFBSFootprinter: a multiomics tool for prediction of transcription factor binding sites in vertebrate speciesSemantic proximity Read

PeakRegressor identifies composite sequence motifs responsible for STAT1 binding sites and their potential rSNPs.Semantic proximity Read

Classification of Human Transcription Factors Based on Their Effector Domains via Unsupervised LearningSemantic proximity Read

Systematic Prediction of Regulatory Motifs from Human ChIP-Sequencing Data Based on a Deep Learning FrameworkSemantic proximity Read

Overlapping binding sites underlie TF genomic occupancySemantic proximity Read

Dissecting the regulatory activity and sequence content of loci with exceptional numbers of transcription factor associationsSemantic proximity Read

Sequence determinants of human gene regulatory elementsSemantic proximity Read