Accelerating Motif Discovery: Motif Matching on Parallel Hardware

2006 ◽  
pp. 197-206 ◽  
Author(s):  
Geir Kjetil Sandve ◽  
Magnar Nedland ◽  
Øyvind Bø Syrstad ◽  
Lars Andreas Eidsheim ◽  
Osman Abul ◽  
...  
Keyword(s):  
Motif Discovery

Genetic Optimization for (l,d)-Motif Discovery

2012 ◽  
Vol 35 (7) ◽  
pp. 1429
Author(s):  
Hong-Wei HUO ◽  
Dan-Dan GUO ◽  
Qiang YU ◽  
Yi-Pu ZHANG ◽  
Wei NIU
Keyword(s):  
Motif Discovery ◽  
Genetic Optimization

scholarly journals CpGmotifs: a tool to discover DNA motifs associated to CpG methylation events

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Giovanni Scala ◽  
Antonio Federico ◽  
Dario Greco
Keyword(s):  
Dna Methylation ◽  
Motif Discovery ◽  
Cpg Methylation ◽  
Functional Interpretation ◽  
Dna Motifs ◽  
Molecular Alterations ◽  
Link Type ◽  
Dna Motif ◽  
Quantitative Manner ◽  
Dna Motif Discovery

Abstract Background The investigation of molecular alterations associated with the conservation and variation of DNA methylation in eukaryotes is gaining interest in the biomedical research community. Among the different determinants of methylation stability, the DNA composition of the CpG surrounding regions has been shown to have a crucial role in the maintenance and establishment of methylation statuses. This aspect has been previously characterized in a quantitative manner by inspecting the nucleotidic composition in the region. Research in this field still lacks a qualitative perspective, linked to the identification of certain sequences (or DNA motifs) related to particular DNA methylation phenomena. Results Here we present a novel computational strategy based on short DNA motif discovery in order to characterize sequence patterns related to aberrant CpG methylation events. We provide our framework as a user-friendly, shiny-based application, CpGmotifs, to easily retrieve and characterize DNA patterns related to CpG methylation in the human genome. Our tool supports the functional interpretation of deregulated methylation events by predicting transcription factors binding sites (TFBS) encompassing the identified motifs. Conclusions CpGmotifs is an open source software. Its source code is available on GitHub https://github.com/Greco-Lab/CpGmotifs and a ready-to-use docker image is provided on DockerHub at https://hub.docker.com/r/grecolab/cpgmotifs.

scholarly journals Transcription factor and microRNA motif discovery: The Amadeus platform and a compendium of metazoan target sets

2008 ◽  
Vol 18 (7) ◽  
pp. 1180-1189 ◽  
Author(s):  
C. Linhart ◽  
Y. Halperin ◽  
R. Shamir
Keyword(s):  
Transcription Factor ◽  
Motif Discovery ◽  
Target Sets

A modified algorithm for variable length DNA motif discovery

2013 ◽  
Author(s):  
S. M. Samiul Islam ◽  
Md. Rashed Asger ◽  
Md. Abid Hasan ◽  
M. Abdul Mottalib
Keyword(s):  
Motif Discovery ◽  
Variable Length ◽  
Dna Motif ◽  
Dna Motif Discovery ◽  
Modified Algorithm

scholarly journals Combining phylogenetic motif discovery and motif clustering to predict co-regulated genes

2005 ◽  
Vol 21 (20) ◽  
pp. 3832-3839 ◽  
Author(s):  
S. T. Jensen ◽  
L. Shen ◽  
J. S. Liu
Keyword(s):  
Motif Discovery ◽  
Motif Clustering

scholarly journals Subgraph ensembles and motif discovery using an alternative heuristic for graph isomorphism

2006 ◽  
Vol 74 (5) ◽  
Author(s):  
Kim Baskerville ◽  
Maya Paczuski
Keyword(s):  
Motif Discovery ◽  
Graph Isomorphism
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