ReviewFrontiers in genetics2016
Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic Cells.
Review in Frontiers in genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.
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92 citing papers in PubMed, 161 citations in OpenAlex.
- Transcriptome-Based Identification ofPlants (Basel, Switzerland) · 2026Article
- Comprehensive Genome-Wide Identification and Expression Analysis of the N6-Methyladenosine (m6A) Regulatory Network Influences Rapid Stress Adaptation With Exogenous Melatonin in Rice.Journal of pineal research · 2026Article
- Review
- Benchmarking transcription factor binding site prediction models: a comparative analysis on synthetic and biological data.Briefings in bioinformatics · 2025Article
- CREATE: cell-type-specific cis-regulatory element identification via discrete embedding.Nature communications · 2025Article
- Identifying associations between short tandem repeat sequences and gene expression in yeast reveals specific repeated motifs encoding transcriptional regulatory proteins.Computational and structural biotechnology journal · 2025Article
- Coactivator networks orchestrating noncanonical AR programs in enzalutamide-resistant CRPC.Frontiers in oncology · 2025Review
- Article
- Promoter Region and Regulatory Elements of IGF and VIP Genes Associated With Reproductive Traits in Chicken.International journal of genomics · 2025Article
- The evaluation of transcription factor binding site prediction tools in human and Arabidopsis genomes.BMC bioinformatics · 2024Article
- Genomic background sequences systematically outperform synthetic ones in de novo motif discovery for ChIP-seq data.NAR genomics and bioinformatics · 2024Article
- Genome wide identification of phenylalanine ammonia-lyase (PAL) gene family in Cucumis sativus (cucumber) against abiotic stress.BMC genomic data · 2024Article
- DNA Transposons Favor De Novo Transcript Emergence Through Enrichment of Transcription Factor Binding Motifs.Genome biology and evolution · 2024Article
- Re-sequencing of the casein genes in Swedish Red cattle giving milk with diverse protein profiles and extreme rennet coagulation properties.JDS communications · 2024Article
- A statistical approach for identifying single nucleotide variants that affect transcription factor binding.iScience · 2024Article
- The extracellular matrix differentially directs myoblast motility and differentiation in distinct forms of muscular dystrophy: Dystrophic matrices alter myoblast motility.Matrix biology : journal of the International Society for Matrix Biology · 2024Article
- Catalase (CAT) Gene Family in Oil Palm (International journal of molecular sciences · 2024Article
- MoCoLo: a testing framework for motif co-localization.Briefings in bioinformatics · 2024Article
- Comprehensive analysis of transcription factor binding sites and expression profiling of rice pathogenesis related genes (Frontiers in plant science · 2024Article
- Position Weight Matrix or Acyclic Probabilistic Finite Automaton: Which model to use? A decision rule inferred for the prediction of transcription factor binding sites.Genetics and molecular biology · 2024Article
32 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Eukaryotic genomes contain a variety of structured patterns: repetitive elements, binding sites of DNA and RNA associated proteins, splice sites, and so on. Often, these structured patterns can be formalized as motifs and described using a proper mathematical model such as position weight matrix and IUPAC consensus. Two key tasks are typically carried out for motifs in the context of the analysis of genomic sequences. These are: identification in a set of DNA regions of over-represented motifs from a particular motif database, and de novo discovery of over-represented motifs. Here we describe existing methodology to perform these two tasks for motifs characterizing transcription factor binding. When applied to the output of ChIP-seq and ChIP-exo experiments, or to promoter regions of co-modulated genes, motif analysis techniques allow for the prediction of transcription factor binding events and enable identification of transcriptional regulators and co-regulators. The usefulness of motif analysis is further exemplified in this review by how motif discovery improves peak calling in ChIP-seq and ChIP-exo experiments and, when coupled with information on gene expression, allows insights into physical mechanisms of transcriptional modulation.
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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.