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- aggregation classification "P1".
- aggregation creator person.
- aggregation creator person.
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- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2014".
- aggregation format "application/pdf".
- aggregation hasFormat 4193767.bibtex.
- aggregation hasFormat 4193767.csv.
- aggregation hasFormat 4193767.dc.
- aggregation hasFormat 4193767.didl.
- aggregation hasFormat 4193767.doc.
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- aggregation isPartOf urn:isbn:9783642551956.
- aggregation isPartOf urn:issn:0302-9743.
- aggregation language "eng".
- aggregation publisher "Springer".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "A parallel, distributed-memory framework for comparative motif discovery".
- aggregation abstract "The increasing number of sequenced organisms has opened new possibilities for the computational discovery of cis-regulatory elements ('motifs') based on phylogenetic footprinting. Word-based, exhaustive approaches are among the best performing algorithms, however, they pose significant computational challenges as the number of candidate motifs to evaluate is very high. In this contribution, we describe a parallel, distributed-memory framework for de novo comparative motif discovery. Within this framework, two approaches for phylogenetic footprinting are implemented: an alignment-based and an alignment-free method. The framework is able to statistically evaluate the conservation of motifs in a search space containing over 160 million candidate motifs using a distributed-memory cluster with 200 CPU cores in a few hours. Software available from http://bioinformatics.intec.ugent.be/blsspeller/".
- aggregation authorList BK147142.
- aggregation endPage "277".
- aggregation startPage "268".
- aggregation volume "8385".
- aggregation aggregates 4193768.
- aggregation aggregates 4193769.
- aggregation isDescribedBy 4193767.
- aggregation similarTo 978-3-642-55195-6_25.
- aggregation similarTo LU-4193767.