- Title
- Dynamically regulated initialization for S-system modelling of genetic networks
- Creator
- Gill, Jaskaran; Chetty, Madhu; Shatte, Adrian; Hallinan, Jennifer
- Date
- 2021
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/188554
- Identifier
- vital:17305
- Identifier
-
https://doi.org/10.1109/CIBCB49929.2021.9562958
- Identifier
- ISBN:9781665401128 (ISBN)
- Abstract
- Reverse engineering of gene regulatory networks through temporal gene expression data is an active area of research. Among the plethora of modelling techniques under investigation is the decoupled S-system model, which attempts to capture the non-linearity of biological systems in detail. For the model, number of parameters to be estimated are significantly high even when the network is of small or medium scale. Thus, the inference process poses a significant computational burden. In this paper, we propose: (1) a novel population initialization technique, Dynamically Regulated Prediction Initialization (DRPI), which utilises prior knowledge of biological gene expression data to create a feedback loop to produce dynamically regulated high-quality individuals for initial population; (2) an adaptive fitness function; and (3) a method for the maintenance of population diversity. The aim of this work is to reduce the computational complexity of the inference algorithm, to speed up the entire process of reverse engineering. The performance of the proposed algorithm was evaluated against a benchmark dataset and compared with other methods from earlier work. The experimental results show that we succeeded in achieving higher accuracy results in lesser fitness evaluations, considerably reducing the computational burden of the inference process. © 2021 IEEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021, Virtual, Online, 13-15 October 2021, 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2021 IEEE
- Subject
- Differential evolution; Gene Regulatory Network; Inference; S-system Model
- Reviewed
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