ArticleBioinformatics (Oxford, England)2016
Motif comparison based on similarity of binding affinity profiles.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors.Nature methods · 2026Article
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- NPBIP: predicting binding preferences of uncharacterized nucleic-acid-binding proteins.Bioinformatics (Oxford, England) · 2026Article
- TRAFICA: an open chromatin language model to improve transcription factor binding affinity prediction.Bioinformatics (Oxford, England) · 2025Article
- Article
- Perspectives on Codebook: sequence specificity of uncharacterized human transcription factors.bioRxiv : the preprint server for biology · 2024Article
- A unified model for interpretable latent embedding of multi-sample, multi-condition single-cell data.Nature communications · 2024Article
- Accurate isoform quantification by joint short- and long-read RNA-sequencing.bioRxiv : the preprint server for biology · 2024Article
- Post-transcriptional dysregulation in autism, schizophrenia, and bipolar disorder.Journal of biomedical research · 2024Article
- A survey on algorithms to characterize transcription factor binding sites.Briefings in bioinformatics · 2023Review
- Article
- Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding.Genome biology · 2022Article
- The geometric influence on the Cys2His2 zinc finger domain and functional plasticity.Nucleic acids research · 2020Article
- Similarity regression predicts evolution of transcription factor sequence specificity.Nature genetics · 2019Article
- High-throughput functional analysis of lncRNA core promoters elucidates rules governing tissue specificity.Genome research · 2019Article
- The Human Transcription Factors.Cell · 2018Review
- Comparison of ChIP-Seq Data and a Reference Motif Set for Human KRAB C2H2 Zinc Finger Proteins.G3 (Bethesda, Md.) · 2018Article
- Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease.Nature communications · 2017Article
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Authors and funding
4 authors.
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Abstract
Measuring motif similarity is essential for identifying functionally related transcription factors (TFs) and RNA-binding proteins, and for annotating de novo motifs. Here, we describe Motif Similarity Based on Affinity of Targets (MoSBAT), an approach for measuring the similarity of motifs by computing their affinity profiles across a large number of random sequences. We show that MoSBAT successfully associates de novo ChIP-seq motifs with their respective TFs, accurately identifies motifs that are obtained from the same TF in different in vitro assays, and quantitatively reflects the similarity of in vitro binding preferences for pairs of TFs. AVAILABILITY AND IMPLEMENTATION: MoSBAT is available as a webserver at mosbat.ccbr.utoronto.ca, and for download at github.com/csglab/MoSBAT. CONTACT: t.hughes@utoronto.ca or hamed.najafabadi@mcgill.caSupplementary information: Supplementary data are available at Bioinformatics online.
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