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Paper Abstract and Keywords
Presentation 2009-12-21 13:25
Improving the inference method of gene regulatory networks using neural networks
Yasuki Hirai, Hiroaki Kurokawa (Tokyo Univ. of Tech.) NLP2009-131
Abstract (in Japanese) (See Japanese page) 
(in English) The regulatory interaction between gene expressions is considered as a universal mechanism in biological systems and such a mechanism of interactions have been modeled as gene regulatory networks. The gene regulatory networks show a correlation among gene expression.
A lot of method to describe gene regulatory networks have been developed. Especially, owing to the technologies such as DNA microarrays which provide a number of time series data of gene expressions, the gene regulatory networks using ordinary differential equations have been proposed and developed in recently.
To infer such a gene regulatory networks using ODEs, it is necessary to approximate many unknown functions from the time series data of gene expressions which is obtained experimentally. Here, one of the successful inference method of the gene regulatory networks is the method using neural network to approximate the unknown functions.
In this study, we propose an improving method to infer the gene regulatory networks using neural network. Simulation results show the validity of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) gene regulatory network / differential equation model / neural network / / / / /  
Reference Info. IEICE Tech. Rep., vol. 109, no. 354, NLP2009-131, pp. 27-32, Dec. 2009.
Paper # NLP2009-131 
Date of Issue 2009-12-14 (NLP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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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Conference Information
Committee NLP  
Conference Date 2009-12-21 - 2009-12-21 
Place (in Japanese) (See Japanese page) 
Place (in English)  
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Paper Information
Registration To NLP 
Conference Code 2009-12-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improving the inference method of gene regulatory networks using neural networks 
Sub Title (in English)  
Keyword(1) gene regulatory network  
Keyword(2) differential equation model  
Keyword(3) neural network  
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1st Author's Name Yasuki Hirai  
1st Author's Affiliation Tokyo University of Technology (Tokyo Univ. of Tech.)
2nd Author's Name Hiroaki Kurokawa  
2nd Author's Affiliation Tokyo University of Technology (Tokyo Univ. of Tech.)
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Speaker Author-2 
Date Time 2009-12-21 13:25:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2009-131 
Volume (vol) vol.109 
Number (no) no.354 
Page pp.27-32 
#Pages
Date of Issue 2009-12-14 (NLP) 


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