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Updated: May 11, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
MEME-LaB: motif analysis in clusters
Paul Brown1, Laura Baxter, Richard Hickman
1Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk
Summary:
Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets.
Availability:
MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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