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Improvements of protein function ann...

Cheng, Gong.

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Improvements of protein function annotations using structures.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Improvements of protein function annotations using structures./
Author:	Cheng, Gong.
Description:	67 p.
Notes:	Adviser: David Baker.
Contained By:	Dissertation Abstracts International69-06B.
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3318170
ISBN:	9780549672975

Improvements of protein function annotations using structures.
Cheng, Gong.

Improvements of protein function annotations using structures. - 67 p.

Adviser: David Baker.

Thesis (Ph.D.)--University of Washington, 2008.

Understanding the function of each gene in the genome is central to life sciences. A large number of high resolution protein structures provide new opportunities for computational and structural biologists. My thesis work is dedicated to elucidating protein functions from protein structures using computational methods. The first part of my work focused on improving sequence based functional site prediction by combining sequence conservation and ROSETTA computational protein design. This method has achieved improved functional site identification accuracy when compared with related work. The web service based on this work is widely used by top research institutes globally. The second part of my research focus aimed to elucidate protein functions using structures as the only source of information. Specifically, I first developed a geometrical knowledge-based scoring function to model protein/ion interactions accurately. Combined with a novel high performance grid based sampling method, protein/ion binding sites can be predicted at high resolution within minutes. Subsequently, I extended the scoring function to handle ion mediated protein/substrate interactions. Then I assembled a carbohydrate rotamer library to annotate lectin functions from solved lectin structures. All of this work demonstrats that protein structures are extremely useful for protein function annotations and more efforts should be put into this field to continue the research described above.

ISBN: 9780549672975Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Improvements of protein function annotations using structures.
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020 $a 9780549672975
035 $a (UMI)AAI3318170
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040 $a UMI $c UMI
100 1 $a Cheng, Gong. $3 1265043
245 1 0 $a Improvements of protein function annotations using structures.
300 $a 67 p.
500 $a Adviser: David Baker.
500 $a Source: Dissertation Abstracts International, Volume: 69-06, Section: B, page: .
502 $a Thesis (Ph.D.)--University of Washington, 2008.
520 $a Understanding the function of each gene in the genome is central to life sciences. A large number of high resolution protein structures provide new opportunities for computational and structural biologists. My thesis work is dedicated to elucidating protein functions from protein structures using computational methods. The first part of my work focused on improving sequence based functional site prediction by combining sequence conservation and ROSETTA computational protein design. This method has achieved improved functional site identification accuracy when compared with related work. The web service based on this work is widely used by top research institutes globally. The second part of my research focus aimed to elucidate protein functions using structures as the only source of information. Specifically, I first developed a geometrical knowledge-based scoring function to model protein/ion interactions accurately. Combined with a novel high performance grid based sampling method, protein/ion binding sites can be predicted at high resolution within minutes. Subsequently, I extended the scoring function to handle ion mediated protein/substrate interactions. Then I assembled a carbohydrate rotamer library to annotate lectin functions from solved lectin structures. All of this work demonstrats that protein structures are extremely useful for protein function annotations and more efforts should be put into this field to continue the research described above.
590 $a School code: 0250.
650 4 $a Biology, Bioinformatics. $3 1018415
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710 2 $a University of Washington. $3 545923
773 0 $t Dissertation Abstracts International $g 69-06B.
790 $a 0250
790 1 0 $a Baker, David, $e advisor
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3318170