Paper Abstract and Keywords |
Presentation |
2011-07-26 15:05
Prediction of Protein O-Glycosylation Sites by Machine Learning and a Study on its Function Ikuko Nishikawa, Masahiro Ito (Ritsumeikan Univ.), Satoshi Fukuchi (Maebashi Inst. Tech.), Keiichi Homma (NIG), Ken Nishikawa NC2011-42 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
{\it O}-glycosylation is one of the important posttranslational modifications of mammalian proteins. We applied a support vector machine (SVM) to predict whether Ser or Thr is glycosylated, aiming at studying the {\it O}-glycosylation mechanism. {\it O}-glycosylated sites are often found in cluster, whereas other sites are located sporadically. Therefore, we developed two types of SVMs for predicting clustered and isolated sites separately. Moreover, we found that the {\it O}-glycosylation sites, especially of the clustered type, are preferentially located within intrinsically disordered regions of proteins, which could be the key feature for understanding the property and the role of {\it O}-glycosylation in functional diversity and structural stability of the biological systems. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Protein O-glycosylation / Prediction / Machine Learning / Support Vector Machine / Intrinsically Disordered Region / / / |
Reference Info. |
IEICE Tech. Rep., vol. 111, no. 157, NC2011-42, pp. 119-122, July 2011. |
Paper # |
NC2011-42 |
Date of Issue |
2011-07-18 (NC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NC2011-42 |
Conference Information |
Committee |
NC |
Conference Date |
2011-07-25 - 2011-07-26 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Graduate School of Engineering, Kobe University |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Intelligent systems and general |
Paper Information |
Registration To |
NC |
Conference Code |
2011-07-NC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Prediction of Protein O-Glycosylation Sites by Machine Learning and a Study on its Function |
Sub Title (in English) |
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Keyword(1) |
Protein O-glycosylation |
Keyword(2) |
Prediction |
Keyword(3) |
Machine Learning |
Keyword(4) |
Support Vector Machine |
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Intrinsically Disordered Region |
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1st Author's Name |
Ikuko Nishikawa |
1st Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
2nd Author's Name |
Masahiro Ito |
2nd Author's Affiliation |
Ritsumeikan University (Ritsumeikan Univ.) |
3rd Author's Name |
Satoshi Fukuchi |
3rd Author's Affiliation |
Maebashi Institute of Technology (Maebashi Inst. Tech.) |
4th Author's Name |
Keiichi Homma |
4th Author's Affiliation |
National Institute of Genetics (NIG) |
5th Author's Name |
Ken Nishikawa |
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Speaker |
Author-1 |
Date Time |
2011-07-26 15:05:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2011-42 |
Volume (vol) |
vol.111 |
Number (no) |
no.157 |
Page |
pp.119-122 |
#Pages |
4 |
Date of Issue |
2011-07-18 (NC) |
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