ArticlePloS one2010
A novel alignment-free method for comparing transcription factor binding site motifs.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Discovering unknown human and mouse transcription factor binding sites and their characteristics from ChIP-seq data.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Graph Theory-Based Sequence Descriptors as Remote Homology Predictors.Biomolecules · 2019Article
- A proximity-based graph clustering method for the identification and application of transcription factor clusters.BMC bioinformatics · 2017Article
- RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.Nucleic acids research · 2017Article
- An efficient algorithm for improving structure-based prediction of transcription factor binding sites.BMC bioinformatics · 2017Article
- Structure-based prediction of transcription factor binding specificity using an integrative energy function.Bioinformatics (Oxford, England) · 2016Article
- Article
- Alignment-free clustering of transcription factor binding motifs using a genetic-k-medoids approach.BMC bioinformatics · 2015Article
- Cofunctional Subpathways Were Regulated by Transcription Factor with Common Motif, Common Family, or Common Tissue.BioMed research international · 2015Article
- Information theory applications for biological sequence analysis.Briefings in bioinformatics · 2014Review
- Identification of novel motif patterns to decipher the promoter architecture of co-expressed genes in Arabidopsis thaliana.BMC systems biology · 2013Article
- A discriminative approach for unsupervised clustering of DNA sequence motifs.PLoS computational biology · 2013Article
- SPIC: a novel similarity metric for comparing transcription factor binding site motifs based on information contents.BMC systems biology · 2013Article
- Efficient large-scale protein sequence comparison and gene matching to identify orthologs and co-orthologs.Nucleic acids research · 2012Article
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2 authors.
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Abstract
backgroundTranscription factor binding site (TFBS) motifs can be accurately represented by position frequency matrices (PFM) or other equivalent forms. We often need to compare TFBS motifs using their PFMs in order to search for similar motifs in a motif database, or cluster motifs according to their binding preference. The majority of current methods for motif comparison involve a similarity metric for column-to-column comparison and a method to find the optimal position alignment between the two compared motifs. In some applications, alignment-free methods might be preferred; however, few such methods with high accuracy have been described. METHODOLOGY/PRINCIPAL
findingsHere we describe a novel alignment-free method for quantifying the similarity of motifs using their PFMs by converting PFMs into k-mer vectors. The motifs could then be compared by measuring the similarity among their corresponding k-mer vectors. CONCLUSIONS/SIGNIFICANCE: We demonstrate that our method in general achieves similar performance or outperforms the existing methods for clustering motifs according to their binding preference and identifying similar motifs of transcription factors of the same family.
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