Paper Abstract and Keywords |
Presentation |
2014-05-26 14:50
Inferring method of the Gene Regulatory Networks using RBF Networks Adopting a Majority Rule Naoyuki Kizaki, Hiroaki Kurokawa (Tokyo Univ. of Tech.) NLP2014-3 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The gene regulatory network(GRN) is the in biological system that describes the interaction of the gene expressions. A lot of inference methods of the GRN have been proposed recently.
The method using the neural networks is one of the valuable conventional method of GRN inference.
In the conventional method, the network is inferred based on the gene expression model described by differential equation and the gene expression model is estimated by function approximation using neural networks.
In the conventional method, the learning algorithm of the neural network requires the iteration process and the convergence dynamics is depend on the problem.
On the other hand, the radial basis function(RBF) network is also well known network that can be used in the function approximation.
The RBF network does not requires the iterative learning process and this feature will lead the reduction of the calculation in inference of the GRN.
In this study, we propose the GRN inference method using the RBF network.
Our proposed method shows good results of the inference time, however, the accuracy is not so good as the conventional method.
Then we apply the majority rule to our proposed method and we show that the proposed method adopting the majority rule improves the accuracy of the inference.
In the simulation, we show the results of the inference of the artificially defined GRN and the practical network using experimental data. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Gene regulatory network / function approximation / RBF network / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 114, no. 55, NLP2014-3, pp. 13-18, May 2014. |
Paper # |
NLP2014-3 |
Date of Issue |
2014-05-19 (NLP) |
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) |
Download PDF |
NLP2014-3 |
Conference Information |
Committee |
NLP |
Conference Date |
2014-05-26 - 2014-05-27 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Big Heart IZUMO |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Nonlinear Problems, etc. |
Paper Information |
Registration To |
NLP |
Conference Code |
2014-05-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Inferring method of the Gene Regulatory Networks using RBF Networks Adopting a Majority Rule |
Sub Title (in English) |
|
Keyword(1) |
Gene regulatory network |
Keyword(2) |
function approximation |
Keyword(3) |
RBF network |
Keyword(4) |
|
Keyword(5) |
|
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Naoyuki Kizaki |
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.) |
3rd Author's Name |
|
3rd Author's Affiliation |
() |
4th Author's Name |
|
4th Author's Affiliation |
() |
5th Author's Name |
|
5th Author's Affiliation |
() |
6th Author's Name |
|
6th Author's Affiliation |
() |
7th Author's Name |
|
7th Author's Affiliation |
() |
8th Author's Name |
|
8th Author's Affiliation |
() |
9th Author's Name |
|
9th Author's Affiliation |
() |
10th Author's Name |
|
10th Author's Affiliation |
() |
11th Author's Name |
|
11th Author's Affiliation |
() |
12th Author's Name |
|
12th Author's Affiliation |
() |
13th Author's Name |
|
13th Author's Affiliation |
() |
14th Author's Name |
|
14th Author's Affiliation |
() |
15th Author's Name |
|
15th Author's Affiliation |
() |
16th Author's Name |
|
16th Author's Affiliation |
() |
17th Author's Name |
|
17th Author's Affiliation |
() |
18th Author's Name |
|
18th Author's Affiliation |
() |
19th Author's Name |
|
19th Author's Affiliation |
() |
20th Author's Name |
|
20th Author's Affiliation |
() |
Speaker |
Author-2 |
Date Time |
2014-05-26 14:50:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
NLP2014-3 |
Volume (vol) |
vol.114 |
Number (no) |
no.55 |
Page |
pp.13-18 |
#Pages |
6 |
Date of Issue |
2014-05-19 (NLP) |
|