Thèses sur le sujet « EST clustering »
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Ptitsyn, Andrey. « New algorithms for EST clustering ». Thesis, University of the Western Cape, 2000. http://etd.uwc.ac.za/index.php?module=etd&.
Texte intégralMoler, James C. « Optimizing Approaches for Sensitive, High Performance Clustering of Gene Expressions ». Miami University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=miami1303482998.
Texte intégralLipták, Zsuzsanna. « Strings in proteomics and transcriptomics algorithmic and combinatorial questions in mass spectrometry and EST clustering / ». [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=979746566.
Texte intégralSczyrba, Alexander. « Genome analysis based on EST collections a clustering pipeline and a database on Xenopus laevis / ». [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=983938016.
Texte intégralGu, Yuhua. « Ant clustering with consensus ». [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0002959.
Texte intégralPrimo, Tiago Thompsen. « M?todos de clusteriza??o para apoio ? classifica??o est?tica de documentos ». Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2008. http://tede2.pucrs.br/tede2/handle/tede/5028.
Texte intégralNeste trabalho ser?o abordados estudos referentes ? classifica??o de grande quantidade de documentos de conte?do vari?vel. Em tal processo quando um grande n?mero de documentos ? gerado, existe a necessidade de um usu?rio verific?-los um a um com a inten??o de separ?-los em bons (com pouco ou nenhum problema estrutural) ou ruins (que possuem problemas estruturais), processo este considerado lento e oneroso. Considerando este problema, neste trabalho foi desenvolvida uma ferramenta de classifica??o est?tica de documentos que visa reduzir esta interven??o humana. A ferramenta desenvolvida ? baseada em m?tricas que avaliam o quanto um documento automaticamente gerado difere de seu template, criando para cada um destes documentos uma assinatura baseada nas t?cnicas de fingerprint, objetivando primeiramente distingui-los entre si para ent?o utilizar t?cnicas de clusteriza??o criando grupos de documentos com caracter?sticas semelhantes. O algoritmo K-Med?ides ? usado para fazer tal agrupamento, tal algoritmo funciona criando grupos de objetos considerando um destes como base para a cria??o de cada cluster. A id?ia deste trabalho ? reduzir a interven??o humana fazendo com que um usu?rio classifique em bom ou ruim apenas determinados documentos de cada grupo formado pelo algoritmo de clusteriza??o. S?o tamb?m apresentados resultados de quatro experimentos realizados com esta ferramenta avaliando as contribui??es para diminuir a interven??o humana no processo de classifica??o de documentos.
Arumugavelu, Shankar. « SIMD algorithms for single link and complete link pattern clustering ». [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0001967.
Texte intégralHore, Prodip. « Scalable frameworks and algorithms for cluster ensembles and clustering data streams ». [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002135.
Texte intégralGupta, Upavan. « Utilitarian approaches for multi-metric optimization in VLSI circuit design and spatial clustering ». [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002584.
Texte intégralLundequist, Per. « Spatial clustering and industrial competitiveness : Studies in economic geography ». Doctoral thesis, Uppsala : Department of Social and Economic Geography, Uppsala University, 2002. http://publications.uu.se/theses/99-2002-0429140456/.
Texte intégralFratesi, Sarah Elizabeth. « The Virtual Landscape of Geological Information Topics, Methods, and Rhetoric in Modern Geology ». [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002777.
Texte intégralOlgun, Muhammet Ertug. « Design And Fpga Implementation Of An Efficient Deinterleaving Algorithm ». Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609816/index.pdf.
Texte intégralRanchod, Pravesh. « Parallelisation of EST clustering ». Thesis, 2006. http://hdl.handle.net/10539/281.
Texte intégralThe field of bioinformatics has been developing steadily, with computational problems related to biology taking on an increased importance as further advances are sought. The large data sets involved in problems within computational biology have dictated a search for good, fast approximations to computationally complex problems. This research aims to improve a method used to discover and understand genes, which are small subsequences of DNA. A difficulty arises because genes contain parts we know to be functional and other parts we assume are non-functional as there functions have not been determined. Isolating the functional parts requires the use of natural biological processes which perform this separation. However, these processes cannot read long sequences, forcing biologists to break a long sequence into a large number of small sequences, then reading these. This creates the computational difficulty of categorizing the short fragments according to gene membership. Expressed Sequence Tag Clustering is a technique used to facilitate the identification of expressed genes by grouping together similar fragments with the assumption that they belong to the same gene. The aim of this research was to investigate the usefulness of distributed memory parallelisation for the Expressed Sequence Tag Clustering problem. This was investigated empirically, with a distributed system tested for speed against a sequential one. It was found that distributed memory parallelisation can be very effective in this domain. The results showed a super-linear speedup for up to 100 processors, with higher numbers not tested, and likely to produce further speedups. The system was able to cluster 500000 ESTs in 641 minutes using 101 processors.
Lipták, Zsuzsanna [Verfasser]. « Strings in proteomics and transcriptomics : algorithmic and combinatorial questions in mass spectrometry and EST clustering / Zsuzsanna Lipták ». 2005. http://d-nb.info/979746566/34.
Texte intégralSczyrba, Alexander [Verfasser]. « Genome analysis based on EST collections : a clustering pipeline and a database on Xenopus laevis / vorgelegt von Alexander Sczyrba ». 2007. http://d-nb.info/983938016/34.
Texte intégralVenkatraman, Anand. « Validation of a novel expressed sequence tag (EST) clustering method and development of a phylogenetic annotation pipeline for livestock gene families ». Thesis, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3112.
Texte intégralVahdat, Ali R. « Symbiotic Evolutionary Subspace Clustering (S-ESC) ». 2013. http://hdl.handle.net/10222/40629.
Texte intégralKalapriya, K. « On The Issues Of Supporting On-Demand Streaming Application Over Peer-to-Peer Networks ». Thesis, 2007. http://hdl.handle.net/2005/536.
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