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Combinatorial approaches to signal f...

Sze, Sing-Hoi.

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Combinatorial approaches to signal finding and gene finding in DNA sequences.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Combinatorial approaches to signal finding and gene finding in DNA sequences./
Author:	Sze, Sing-Hoi.
Description:	76 p.
Notes:	Source: Dissertation Abstracts International, Volume: 63-02, Section: B, page: 0883.
Contained By:	Dissertation Abstracts International63-02B.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3041530
ISBN:	0493550100

Combinatorial approaches to signal finding and gene finding in DNA sequences.
Sze, Sing-Hoi.

Combinatorial approaches to signal finding and gene finding in DNA sequences. - 76 p.

Source: Dissertation Abstracts International, Volume: 63-02, Section: B, page: 0883.

Thesis (Ph.D.)--University of Southern California, 2000.

In this thesis, we develop combinatorial approaches to two important problems in computational biology: signal finding and gene finding in DNA sequences.

ISBN: 0493550100Subjects--Topical Terms:

626642
Computer Science.

Combinatorial approaches to signal finding and gene finding in DNA sequences.
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100 1 $a Sze, Sing-Hoi. $3 1939555
245 1 0 $a Combinatorial approaches to signal finding and gene finding in DNA sequences.
300 $a 76 p.
500 $a Source: Dissertation Abstracts International, Volume: 63-02, Section: B, page: 0883.
500 $a Adviser: Pavel A. Pevzner.
502 $a Thesis (Ph.D.)--University of Southern California, 2000.
520 $a In this thesis, we develop combinatorial approaches to two important problems in computational biology: signal finding and gene finding in DNA sequences.
520 $a Signal finding (pattern discovery in unaligned DNA sequences) is a fundamental problem in both computer science and molecular biology with important applications in locating regulatory sites and drug target identification. Despite many studies, this problem is far from being solved: most signals in DNA sequences are so complicated that we don't yet have good models or reliable algorithms for their recognition. We complement existing statistical and machine learning approaches to this problem by combinatorial approaches that proved to be successful in identifying very subtle signals. This work appears in "Pevzner P. A. and Sze S.-H. (2000). Combinatorial approaches to finding subtle signals in DNA sequences. In Proc. of the 8th Int. Conf. on Intelligent Systems for Mol. Biol. (ISMB'2000), 269--278."
520 $a Gene finding (determination of splicing site locations in genomic DNA sequences) is an important problem in molecular biology. We describe three different approaches we have developed to aid the gene finding process. This work appears in "Sze S.-H. and Pevzner P. A. (1997). Las Vegas algorithms for gene recognition: suboptimal and errortolerant spliced alignment. J. Comp. Biol., 4, 297--309"; "Sze S.-H., Roytberg M. A., Gelfand M. S., Mironov A. A., Astakhova T. V. and Pevzner P. A. (1998). Algorithms and software for support of gene identification experiments. Bioinformatics, 14, 14--19"; and "Xu G., Sze S.-H., Liu C.-P., Pevzner P. A. and Arnheim N. (1998). Gene hunting without sequencing genomic clones: finding exon boundaries in cDNAs. Genomics, 47, 171--179."
590 $a School code: 0208.
650 4 $a Computer Science. $3 626642
650 4 $a Biology, Molecular. $3 1017719
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690 $a 0307
710 2 0 $a University of Southern California. $3 700129
773 0 $t Dissertation Abstracts International $g 63-02B.
790 1 0 $a Pevzner, Pavel A., $e advisor
790 $a 0208
791 $a Ph.D.
792 $a 2000
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3041530