- Title
- On the reconstruction of genetic network from partial microarray data
- Creator
- Chowdhury, Ahsan; Chetty, Madhu; Nguyen, Vinh
- Date
- 2012
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/157203
- Identifier
- vital:11536
- Identifier
-
https://doi.org/10.1007/978-3-642-34475-6_83
- Identifier
- ISBN: 978-3-642-34474-9
- Abstract
- Gene Regulatory Network (GRN) contains interactions occurring between transcription factors (TF) and target genes which are captured during the microarray creation. However, information about the interactions among microRNAs (miRNA) and target genes can not be captured by current microarray technology. To overcome this limitation, we propose a new technique to reverse engineer GRN from partial microarray data which represent target genes' interactions only. Using S-System model, the approach is modified to incorporate the unavailability of information about miRNA-target genes interactions. The most versatile Differential Evolutionary algorithm is used for optimization and parameter learning. Experimental studies on three newly created synthetic networks, and one real network of Saccharomycescerevisiae called IRMA network, show significant improvement compared to traditional S-System based approach.
- Publisher
- ACM
- Relation
- 19th international conference on Neural Information Processing, ICONIP'12, Doha, Qatar; In Neural Information Processing - Volume Part I (Lecture Notes in Computer Science series) Vol. 7663 , p.689-696 p. 689-696
- Rights
- Copyright ACM
- Rights
- This metadata is freely available under a CCO license
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