- Title
- Reverse engineering genetic networks with time-delayed S-system model and pearson correlation coefficient
- Creator
- Chowdhury, Ahsan; Chetty, Madhu; Nguyen, Vinh
- Date
- 2013
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/157271
- Identifier
- vital:11539
- Identifier
-
https://doi.org/10.1007/978-3-642-42042-9_77
- Identifier
- ISBN: 978-364242041-2
- Abstract
- In almost all biological systems including genetic networks, the complex simultaneous interactions occurring amongst different organelles within a cell are both - instantaneous and time-delayed. Among the various modeling approaches, applied for inferring Gene Regulatory Network (GRN), recently proposed Time-delayed S-System Model (TDSS) is capable of simultaneously represent both the instantaneous and time-delayed interactions. While the delay parameters are incorporated in the S-System model to propose TDSS, this open a new challenge in GRN reconstruction. This paper proposes a systematic approach to fit in various level of knowledge in the delay parameters during the reverse engineering process. Further, we have approximated the delay parameters with well-known statistical measure Pearson correlation coefficient. Experimental studies have been carried out considering two widely used synthetic networks with various delays and real-life network of Saccharomyces cerevisiae called IRMA. The results clearly exhibit the influence of incorporating knowledge in the parameter learning process. © Springer-Verlag 2013.
- Publisher
- Springer
- Relation
- 20th International Conference on Neural Information Processing, ICONIP 2013; Daegu; South Korea; 3rd-7th November 2013; published in Neural Information Processing, Lecture Notes in Computer Science, vol 8227. p. 624-631
- Rights
- Copyright Springer
- Rights
- This metadata is freely available under a CCO license
- Subject
- Pearson correlation coefficient; Reverse engineering; Time-delay
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