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BioMed Research International
Volume 2013 (2013), Article ID 703849, 15 pages
Research Article

A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

1Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany
2Laboratory of Systems Tumor Immunology, Department of Dermatology, Faculty of Medicine, University of Erlangen-Nuremberg, Ulmenweg 18, 91054 Erlangen, Germany
3Department of Dermatology, Venereology and Allergology, University of Leipzig, 04155 Leipzig, Germany
4Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch 7600, South Africa

Received 31 July 2013; Revised 12 September 2013; Accepted 17 September 2013

Academic Editor: Tao Huang

Copyright © 2013 Xin Lai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.