DocumentCode :
2192802
Title :
Parametric Templates: A New Enzyme Active-Site Prediction Algorithm
Author :
Kato, Tsuyoshi ; Suwa, Kazuhiro ; Nagano, Nozomi
Author_Institution :
Grad. Sch. of Eng., Gunma Univ., Kiryu, Japan
fYear :
2010
fDate :
13-13 Dec. 2010
Firstpage :
711
Lastpage :
718
Abstract :
It is an important problem to find functionally analogous enzymes based on the local structures of active-sites. Conventional methods predict active-sites by computing the deviations from the local-structure templates with no statistical parameters. We present a new statistical algorithm that uses parametric templates to compute the deviations of local sites. The parameters of the templates are determined automatically from a set of known active-sites. In this work, promising experimental results are shown through comparison of parametric templates with conventional templates.
Keywords :
biology computing; enzymes; proteins; statistical analysis; enzyme active site prediction algorithm; local sites; parametric templates; statistical algorithm; RLCP classification; active-site prediction; machine learning; parametric template; structural analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-9244-2
Electronic_ISBN :
978-0-7695-4257-7
Type :
conf
DOI :
10.1109/ICDMW.2010.176
Filename :
5693366
Link To Document :
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