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A computational method for genomic s...

Kostem, Emrah.

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A computational method for genomic sequence analysis.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A computational method for genomic sequence analysis./
Author:	Kostem, Emrah.
Description:	69 p.
Notes:	Source: Masters Abstracts International, Volume: 42-05, page: 1755.
Contained By:	Masters Abstracts International42-05.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1419239

A computational method for genomic sequence analysis.
Kostem, Emrah.

A computational method for genomic sequence analysis. - 69 p.

Source: Masters Abstracts International, Volume: 42-05, page: 1755.

Thesis (M.S.Eng.)--University of Massachusetts Lowell, 2004.

The ability to efficiently process large data sets, as in the case of available huge genomic data, is a challenging task. In particular for bioinformatics applications such as similarity searches in a genomic database, an abundance of data in the form of nucleotides or amino acids is likely to exist. There is a need and a desire to realize effectiveness in bioinformatics applications, decreasing the complexity of sequence comparison algorithms and tools, used in computational biology. The amount of time needed to analyze genomic sequences plays a key role in the accuracy and biological meaning of the results obtained.Subjects--Topical Terms:

626642
Computer Science.

A computational method for genomic sequence analysis.
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035 $a (UnM)AAI1419239
035 $a AAI1419239
040 $a UnM $c UnM
100 1 $a Kostem, Emrah. $3 1951911
245 1 2 $a A computational method for genomic sequence analysis.
300 $a 69 p.
500 $a Source: Masters Abstracts International, Volume: 42-05, page: 1755.
502 $a Thesis (M.S.Eng.)--University of Massachusetts Lowell, 2004.
520 $a The ability to efficiently process large data sets, as in the case of available huge genomic data, is a challenging task. In particular for bioinformatics applications such as similarity searches in a genomic database, an abundance of data in the form of nucleotides or amino acids is likely to exist. There is a need and a desire to realize effectiveness in bioinformatics applications, decreasing the complexity of sequence comparison algorithms and tools, used in computational biology. The amount of time needed to analyze genomic sequences plays a key role in the accuracy and biological meaning of the results obtained.
520 $a Based on the pioneering work in [1], [2] and through a mapping process, the ability to (1) recognize shapes, and (2) concisely represent the shape of large data using a set of coefficient derived in the mapping process was demonstrated. In [35] [36] [37] [38] [39] it was demonstrated how this method was applied to object representation and recognition, fingerprint, facial, and large data representation and recognition. In this thesis we illustrate how these previous results can be applied to process and analyze genomic data. In particular, in the approach outlined herein, a syntactic representation is formed for genomic sequences whose representation we desire to extract and reproduce compactly. We present the problems and solutions of sequence similarity comparisons in this reduced space. Finally, we show the affect of the nucleotide location on the similarity results and the effect of additional gap information to the phylogeny of the sequences. This research will find applications in the areas of Sequence Analysis, Classification, Phylogenetics, and Drug-Discovery.
590 $a School code: 0111.
650 4 $a Computer Science. $3 626642
650 4 $a Biology, Genetics. $3 1017730
650 4 $a Biology, Molecular. $3 1017719
690 $a 0984
690 $a 0369
690 $a 0307
710 2 0 $a University of Massachusetts Lowell. $3 1017839
773 0 $t Masters Abstracts International $g 42-05.
790 $a 0111
791 $a M.S.Eng.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1419239