Abstract
Inferring gene regulatory networks (GRN) from microarray gene expression data is a highly challenging problem in computational and systems biology. To make GRN reconstruction process more accurate and faster, in this paper, we develop a technique to identify the gene having maximum in-degree in the network using the temporal correlation of gene expression profiles. The in-degree of the identified gene is estimated applying evolutionary optimization algorithm on a decoupled S-system GRN model. The value of in-degree thus obtained is set as the maximum in-degree for inference of the regulations in other genes. The simulations are carried out on in silico networks of small and medium sizes. The results show that both the prediction accuracy in terms of well known performance metrics and the computational time of the optimization process have been improved when compared with the traditional S-system model based inference.
Original language | English |
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Title of host publication | Neural Information Processing |
Subtitle of host publication | 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV |
Publisher | Springer |
Pages | 479-487 |
Number of pages | 9 |
Volume | 9947 LNCS |
ISBN (Print) | 9783319466866 |
DOIs | |
Publication status | Published - 2016 |
Event | International Conference on Neural Information Processing 2016 - Kyoto, Japan Duration: 16 Oct 2016 → 21 Oct 2016 Conference number: 23rd https://link.springer.com/book/10.1007/978-3-319-46687-3 (Proceedings) |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9947 LNCS |
ISSN (Print) | 03029743 |
ISSN (Electronic) | 16113349 |
Conference
Conference | International Conference on Neural Information Processing 2016 |
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Abbreviated title | ICONIP 2016 |
Country/Territory | Japan |
City | Kyoto |
Period | 16/10/16 → 21/10/16 |
Internet address |
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Keywords
- Differential evolution
- Discrete cosine transform
- Gene regulatory network
- S-system
- Temporal correlation