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Automated splice site analysis.
~
Nalla, Vijay Kumar Reddy.
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Automated splice site analysis.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Automated splice site analysis./
作者:
Nalla, Vijay Kumar Reddy.
面頁冊數:
81 p.
附註:
Source: Masters Abstracts International, Volume: 43-06, page: 2284.
Contained By:
Masters Abstracts International43-06.
標題:
Computer Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1426212
ISBN:
0542068923
Automated splice site analysis.
Nalla, Vijay Kumar Reddy.
Automated splice site analysis.
- 81 p.
Source: Masters Abstracts International, Volume: 43-06, page: 2284.
Thesis (M.S.)--University of Missouri - Kansas City, 2005.
Information theory-based software tools have been useful in interpreting noncoding sequence variation within functional sequence elements such as splice sites. Individual information analysis detects activated cryptic splice sites and associated splicing regulatory sites and is capable of distinguishing null from partially functional alleles. We present a server (https://splice.cmh.edu) designed to analyze splicing mutations in binding sites in either human genes, genome-mapped mRNAs, user-defined sequences, or dbSNP entries. Standard HUGO-approved gene symbols and HGVS-approved systematic mutation nomenclature (or dbSNP format) are entered via a web portal. The software was validated by analyzing ∼1,300 mutations from Human Mutation as well as eight mapped SNPs from dbSNP designated as splice site variants. All of the splicing mutations and variants affected splice site strength or activated cryptic splice sites. The server also detected several missense mutations that were unexpectedly predicted to have concomitant effects on splicing. The server also predicts the relative use of different cryptic sites based on total exon splicing information.
ISBN: 0542068923Subjects--Topical Terms:
626642
Computer Science.
Automated splice site analysis.
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Information theory-based software tools have been useful in interpreting noncoding sequence variation within functional sequence elements such as splice sites. Individual information analysis detects activated cryptic splice sites and associated splicing regulatory sites and is capable of distinguishing null from partially functional alleles. We present a server (https://splice.cmh.edu) designed to analyze splicing mutations in binding sites in either human genes, genome-mapped mRNAs, user-defined sequences, or dbSNP entries. Standard HUGO-approved gene symbols and HGVS-approved systematic mutation nomenclature (or dbSNP format) are entered via a web portal. The software was validated by analyzing ∼1,300 mutations from Human Mutation as well as eight mapped SNPs from dbSNP designated as splice site variants. All of the splicing mutations and variants affected splice site strength or activated cryptic splice sites. The server also detected several missense mutations that were unexpectedly predicted to have concomitant effects on splicing. The server also predicts the relative use of different cryptic sites based on total exon splicing information.
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