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A segmentation algorithm for consens...

Wang, Yan.

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A segmentation algorithm for consensus regions in biosequences.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A segmentation algorithm for consensus regions in biosequences./
Author:	Wang, Yan.
Description:	120 p.
Notes:	Source: Masters Abstracts International, Volume: 42-01, page: 0270.
Contained By:	Masters Abstracts International42-01.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ80204
ISBN:	0612802043

A segmentation algorithm for consensus regions in biosequences.
Wang, Yan.

A segmentation algorithm for consensus regions in biosequences. - 120 p.

Source: Masters Abstracts International, Volume: 42-01, page: 0270.

Thesis (M.Sc.)--University of Guelph (Canada), 2003.

The availability of large number of protein sequences and functionality information in many biological resources provides an opportunity for detailed analysis of biomolecules. Many biological and biochemical properties are reflected by molecular regions, rather than a single molecular point. Statistical patterns, defined in various ways, have been demonstrated to be very flexible in evaluating complex relationships between biological functions or molecular structure of a protein and its sequence. In this research, we develop a method to specify statistical complex patterns for segmentation. An algorithm and criteria for detecting consensus regions will be presented. The algorithm analyzes positional statistical complex patterns, and divides the sequence into sequential regions based on these patterns. In the experiments, tumor suppressor p53 is examined using aligned sequences from 31 species. The results show significant association between the consensus regions and (1) the 3D molecular structure, (2) point mutations characteristics in cancer patients. Similar relationship with 3D molecular structure is also found in additional experiments on lysozyme.

ISBN: 0612802043Subjects--Topical Terms:

626642
Computer Science.

A segmentation algorithm for consensus regions in biosequences.
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020 $a 0612802043
035 $a (UnM)AAIMQ80204
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040 $a UnM $c UnM
100 1 $a Wang, Yan. $3 1021976
245 1 0 $a A segmentation algorithm for consensus regions in biosequences.
300 $a 120 p.
500 $a Source: Masters Abstracts International, Volume: 42-01, page: 0270.
500 $a Adviser: David K. Y. Chiu.
502 $a Thesis (M.Sc.)--University of Guelph (Canada), 2003.
520 $a The availability of large number of protein sequences and functionality information in many biological resources provides an opportunity for detailed analysis of biomolecules. Many biological and biochemical properties are reflected by molecular regions, rather than a single molecular point. Statistical patterns, defined in various ways, have been demonstrated to be very flexible in evaluating complex relationships between biological functions or molecular structure of a protein and its sequence. In this research, we develop a method to specify statistical complex patterns for segmentation. An algorithm and criteria for detecting consensus regions will be presented. The algorithm analyzes positional statistical complex patterns, and divides the sequence into sequential regions based on these patterns. In the experiments, tumor suppressor p53 is examined using aligned sequences from 31 species. The results show significant association between the consensus regions and (1) the 3D molecular structure, (2) point mutations characteristics in cancer patients. Similar relationship with 3D molecular structure is also found in additional experiments on lysozyme.
590 $a School code: 0081.
650 4 $a Computer Science. $3 626642
650 4 $a Biology, Molecular. $3 1017719
690 $a 0984
690 $a 0307
710 2 0 $a University of Guelph (Canada). $3 1018650
773 0 $t Masters Abstracts International $g 42-01.
790 1 0 $a Chiu, David K. Y., $e advisor
790 $a 0081
791 $a M.Sc.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ80204