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DEME specifications


Unique identifier OMICS_25360
Alternative name Discriminatively Enhanced Motif Elicitation
Software type Application/Script
Interface Command line interface
Restrictions to use Academic or non-commercial use
Input data Two sets of sequences.
Operating system Unix/Linux
Computer skills Advanced
Maintained Yes


No version available


  • person_outline Timothy L. Bailey
  • person_outline Emma Readhead

Publication for Discriminatively Enhanced Motif Elicitation

DEME citations


Discriminative Motif Discovery via Simulated Evolution and Random Under Sampling

PLoS One
PMCID: 3923751
PMID: 24551063
DOI: 10.1371/journal.pone.0087670

[…] od to accelerate the algorithm, but it does not work well on motifs with large gaps in the middle.Few investigations have been done on the discriminative motif discovery methods in protein sequences. DEME applies substring retrieval followed by branching discovery to find seed motifs in the global search, refines the data model based on the seed motifs in the local search and combines these to fi […]


Sequence Based Classification Using Discriminatory Motif Feature Selection

PLoS One
PMCID: 3213122
PMID: 22102890
DOI: 10.1371/journal.pone.0027382

[…] other motif finders, scorers, or classifiers. For example, in some applications it may be more fruitful to use a different classifier (such as gradient boosting) or a different motif finder (such as DEME ). The data flow would be exactly as in , but with different plugins.In developing our computational pipeline, we opted to emphasize modularity, and this results in some limitations. Allowing eas […]


AMD, an Automated Motif Discovery Tool Using Stepwise Refinement of Gapped Consensuses

PLoS One
PMCID: 3171486
PMID: 21931761
DOI: 10.1371/journal.pone.0024576

[…] Other motif discovery tools improve performance by using discriminative algorithms, which take into account negative sets in the analysis. Members of this type of motif discovery tools include DME , DEME and MoAn .In addition, the algorithms used in most of the motif discovery tools are mainly designed to discover un-gapped motifs, which are usually less than 12 nt long. This restriction is larg […]


De Novo Discovery of Differentially Abundant Transcription Factor Binding Sites Including Their Positional Preference

PLoS Comput Biol
PMCID: 3037384
PMID: 21347314
DOI: 10.1371/journal.pcbi.1001070

[…] In this section, we first evaluate the performance of Dispom on the motif level using the metazoan compendium. Second, we compare the performance of the seven de-novo discovery tools A-GLAM, DEME, DME, Gibbs Sampler, Improbizer, MEME, and Weeder with that of Dispom on the BS level utilizing 18 benchmark data sets containing experimentally verified BSs. Finally, we apply Dispom to a situat […]


PhyloGibbs MP: Module Prediction and Discriminative Motif Finding by Gibbs Sampling

PLoS Comput Biol
PMCID: 2518514
PMID: 18769735
DOI: 10.1371/journal.pcbi.1000156

[…] Discriminative motif-finding has been discussed in the literature previously. We choose three previously published programs, ALSE , Dips , and DEME , which are available for downloading and running locally, to benchmark against PhyloGibbs-MP. Other published programs, not available for download, include LearnPSSM , DME , and dPattern .Unlike […]


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DEME institution(s)
Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
DEME funding source(s)
Supported by NIH Grant NIH R0-1 RR021692-01.

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