ArticleBioinformatics (Oxford, England)2011
DECOD: fast and accurate discriminative DNA motif finding.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed.
- Efficient Storage and Analysis of Genomic Data: A k-mer Frequency Mapping and Image Representation Method.Interdisciplinary sciences, computational life sciences · 2025Article
- The grapevine (Vitis vinifera L.) floral transcriptome in Pinot noir variety: identification of tissue-related gene networks and whorl-specific markers in pre- and post-anthesis phases.Horticulture research · 2021Article
- Differential gene expression identifies a transcriptional regulatory network involving ER-alpha and PITX1 in invasive epithelial ovarian cancer.BMC cancer · 2021Article
- Identification of Cis-Regulatory Sequences Controlling Pollen-Specific Expression of Hydroxyproline-Rich Glycoprotein Genes inPlants (Basel, Switzerland) · 2020Article
- Prediction pipeline for discovery of regulatory motifs associated with Brugia malayi molting.PLoS neglected tropical diseases · 2020Article
- Sex chromosome evolution in parasitic nematodes of humans.Nature communications · 2020Article
- Set cover-based methods for motif selection.Bioinformatics (Oxford, England) · 2020Article
- ProSampler: an ultrafast and accurate motif finder in large ChIP-seq datasets for combinatory motif discovery.Bioinformatics (Oxford, England) · 2019Article
- SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing.Bioinformatics (Oxford, England) · 2019Article
- FisherMP: fully parallel algorithm for detecting combinatorial motifs from large ChIP-seq datasets.DNA research : an international journal for rapid publication of reports on genes and genomes · 2019Article
- Systematic identification of factors mediating accelerated mRNA degradation in response to changes in environmental nitrogen.PLoS genetics · 2018Article
- WSMD: weakly-supervised motif discovery in transcription factor ChIP-seq data.Scientific reports · 2017Article
- A synergistic DNA logic predicts genome-wide chromatin accessibility.Genome research · 2016Article
- Varying levels of complexity in transcription factor binding motifs.Nucleic acids research · 2015Article
- KGCAK: a K-mer based database for genome-wide phylogeny and complexity evaluation.Biology direct · 2015Article
- The p53 C terminus controls site-specific DNA binding and promotes structural changes within the central DNA binding domain.Molecular cell · 2015Article
- Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.PloS one · 2015Article
- De novo prediction of cis-regulatory elements and modules through integrative analysis of a large number of ChIP datasets.BMC genomics · 2014Article
- Binding site discovery from nucleic acid sequences by discriminative learning of hidden Markov models.Nucleic acids research · 2014Article
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9 authors.
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Abstract
motivationMotif discovery is now routinely used in high-throughput studies including large-scale sequencing and proteomics. These datasets present new challenges. The first is speed. Many motif discovery methods do not scale well to large datasets. Another issue is identifying discriminative rather than generative motifs. Such discriminative motifs are important for identifying co-factors and for explaining changes in behavior between different conditions.
resultsTo address these issues we developed a method for DECOnvolved Discriminative motif discovery (DECOD). DECOD uses a k-mer count table and so its running time is independent of the size of the input set. By deconvolving the k-mers DECOD considers context information without using the sequences directly. DECOD outperforms previous methods both in speed and in accuracy when using simulated and real biological benchmark data. We performed new binding experiments for p53 mutants and used DECOD to identify p53 co-factors, suggesting new mechanisms for p53 activation. AVAILABILITY: The source code and binaries for DECOD are available at http://www.sb.cs.cmu.edu/DECOD CONTACT: zivbj@cs.cmu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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