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Dissertations / Theses on the topic 'EST clustering'

Author: Grafiati
Published: 11 March 2023

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1

Ptitsyn, Andrey. "New algorithms for EST clustering." Thesis, University of the Western Cape, 2000. http://etd.uwc.ac.za/index.php?module=etd&amp.

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Expressed sequence tag database is a rich and fast growing source of data for gene expression analysis and drug discovery. Clustering of raw EST data is a necessary step for further analysis and one of the most challenging problems of modem computational biology.
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2

Moler, 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.

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3

Lipták, 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.

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4

Sczyrba, 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.

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5

Gu, Yuhua. "Ant clustering with consensus." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0002959.

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6

Primo, 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.

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Made available in DSpace on 2015-04-14T14:49:01Z (GMT). No. of bitstreams: 1 406128.pdf: 16056423 bytes, checksum: d4b22e3a871de544238db5630e9a295f (MD5) Previous issue date: 2008-03-24<br>Neste 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
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7

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.

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8

Hore, 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.

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9

Gupta, 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.

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10

Lundequist, 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/.

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11

Fratesi, 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.

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12

Olgun, 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.

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In this work, a new deinterleaving algorithm that can be used as a part of an ESM system and its implementation by using an FPGA is studied. The function of the implemented algorithm is interpreting the complex electromagnetic military field in order to detect and determine different RADARs and their types by using incoming RADAR pulses and their PDWs. It is assumed that RADAR signals in the space are received clearly and PDW of each pulse is generated as an input to the implemented algorithm system. Clustering analysis and a new interpreting process is used to deinterleave the RADAR pulses. I
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13

Ranchod, Pravesh. "Parallelisation of EST clustering." Thesis, 2006. http://hdl.handle.net/10539/281.

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Master of Science - Science<br>The 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
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14

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.

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15

Sczyrba, 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.

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16

Venkatraman, 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.

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Prediction of functions of genes in a genome is a key step in all genome sequencing projects. Sequences that carry out important functions are likely to be conserved between evolutionarily distant species and can be identified using cross-species comparisons. In the absence of completed genomes and the accompanying high-quality annotations, expressed sequence tags (ESTs) from random cDNA clones are the primary tools for functional genomics. EST datasets are fragmented and redundant, necessitating clustering of ESTs into groups that are likely to have been derived from the same genes. EST clust
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17

Vahdat, Ali R. "Symbiotic Evolutionary Subspace Clustering (S-ESC)." 2013. http://hdl.handle.net/10222/40629.

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Subspace clustering identifies the attribute support for each cluster as well as identifying the location and number of clusters. In the most general case, attributes associated with each cluster could be unique. A multi-objective evolutionary method is proposed to identify the unique attribute support of each cluster while detecting its data instances. The proposed algorithm, Symbiotic Evolutionary Subspace Clustering (S-ESC) borrows from symbiosis in the sense that each clustering solution is defined in terms of a host, which is formed by a number of co-evolved cluster centroids (or symbiont
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18

Kalapriya, 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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Bandwidth and resource constraints at the server side is a limitation for deployment of streaming media applications. Resource constraints at the server side often leads to saturation of resources during sudden increase in requests. End System Multicast (ESM) is used to overcome the problem of resource saturation. Resources such as storage, bandwidth available at the end systems are utilized to deliver streaming media. In ESM, the end-systems (also known as peers) form a network which is commonly known as Peer-to-Peer (P2P) network. These peers that receive the stream in turn act as routable c
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