DocumentCode :
2498200
Title :
MEET: Motif elements estimation toolkit
Author :
Pairó, Erola ; Maynou, Joan ; Vallverdú, Montserrat ; Caminal, Pere ; Marco, Santiago ; Perera, Alexandre
Author_Institution :
Inst. of Bioeng. of Catalonia, Barcelona, Spain
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
6483
Lastpage :
6486
Abstract :
MEET is an R package that integrates a set of algorithms for the detection of transcription factor binding sites (TFBS). The MEET R package includes five motif searching algorithms: MEME/MAST(Multiple Expectation-Maximization for Motif Elicitation), Q-residuals, MDscan (Motif Discovery scan), ITEME (Information Theory Elements for Motif Estimation) and MATCH. In addition MEET allows the user to work with different alignment algorithms: MUSCLE (Multiple Sequence Comparison by Log-Expectation), ClustalW and MEME. The package can work in two modes, training and detection. The training mode allows the user to choose the best parameters of a detector. Once the parameters are chosen, the detection mode allows to analyze a genome looking for binding sites. Both modes can combine the different alignment and detection methods, offering multiple possibilities. Combining the alignments and the detection algorithms makes possible the comparison between detection models at the same level, without having to care about the differences produced during the alignment process. The MEET R package can be downloaded from http://sisbio.recerca.upc.edu/R/MEET_1.0. tar.gz.
Keywords :
biological techniques; biology computing; data analysis; expectation-maximisation algorithm; genetics; molecular biophysics; molecular configurations; software packages; ClustalW; ITEME; Information Theory Elements for Motif Estimation; MATCH; MDscan; MEET R package; MEME-MAST; MUSCLE; Motif Discovery scan; Motif Elements Estimation Toolkit; Multiple Expectation-Maximization for Motif Elicitation; Multiple Sequence Comparison by Log-Expectation; Q-residuals; TFBS; genome binding sites; motif searching algorithms; transcription factor binding site detection; Bioinformatics; DNA; Detectors; Entropy; Muscles; Training; Vectors; Algorithms; Amino Acid Motifs; Area Under Curve; Binding Sites; Computational Biology; Genes, Fungal; Genome; Probability; Programming Languages; Promoter Regions, Genetic; ROC Curve; Saccharomyces cerevisiae; Sequence Alignment; Sequence Analysis, DNA; Sequence Analysis, Protein; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6091600
Filename :
6091600
Link To Document :
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