- Title
- Exploiting temporal genetic correlations for enhancing regulatory network optimization
- Creator
- Youseph, Ahammed; Chetty, Madhu; Karmakar, Gour
- Date
- 2016
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/104297
- Identifier
- vital:11054
- Identifier
-
https://doi.org/10.1007/978-3-319-46687-3_53
- Identifier
- ISBN:03029743 (ISSN); 9783319466866 (ISBN)
- 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. © Springer International Publishing AG 2016.; Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Publisher
- Springer Verlag
- Relation
- 23rd International Conference on Neural Information Processing, ICONIP 2016; Kyoto, Japan; 16th-21st October 2016; published in Neural Information Processing (Lecture Notes in Computer Science series) Vol. 9947 LNCS, p. 479-487
- Rights
- Copyright © Springer International Publishing AG 2016.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 08 Information and Computing Sciences; Differential evolution; Discrete cosine transform; Gene regulatory network; S-system; Temporal correlation
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