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A segmentation algorithm for consens...

Wang, Yan.

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A segmentation algorithm for consensus regions in biosequences.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A segmentation algorithm for consensus regions in biosequences./
作者:	Wang, Yan.
面頁冊數:	120 p.
附註:	Source: Masters Abstracts International, Volume: 42-01, page: 0270.
Contained By:	Masters Abstracts International42-01.
標題:	Computer Science. -
電子資源:	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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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.
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