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BioMed Research International
Volume 2013 (2013), Article ID 703849, 15 pages
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.
- A. E. Pasquinelli, “MicroRNAs and their targets: recognition, regulation and an emerging reciprocal relationship,” Nature Reviews Genetics, vol. 13, no. 4, pp. 271–282, 2012.
- J. Vera, X. Lai, U. Schmitz, and O. Wolkenhauer, “MicroRNA-regulated networks: the perfect storm for classical molecular biology, the ideal scenario for systems biology,” Advances in Experimental Medicine and Biology, vol. 774, pp. 55–76, 2013.
- S. Nikolov, J. Vera, U. Schmitz, and O. Wolkenhauer, “A model-based strategy to investigate the role of microRNA regulation in cancer signalling networks,” Theory in Biosciences, vol. 130, no. 1, pp. 55–69, 2011.
- X. Lai, U. Schmitz, S. K. Gupta et al., “Computational analysis of target hub gene repression regulated by multiple and cooperative miRNAs,” Nucleic Acids Research, vol. 40, no. 18, pp. 8818–8834, 2012.
- X. Lai, O. Wolkenhauer, and J. Vera, “Modeling miRNA regulation in cancer signaling systems: miR-34a regulation of the p53/Sirt1 signaling module,” Methods in Molecular Biology, vol. 880, pp. 87–108, 2012.
- C. Jiang, Z. Xuan, F. Zhao, and M. Q. Zhang, “TRED: a transcriptional regulatory element database, new entries and other development,” Nucleic Acids Research, vol. 35, supplement 1, pp. D137–D140, 2007.
- L. A. Bovolenta, M. L. Acencio, and N. Lemke, “HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions,” BMC Genomics, vol. 13, article 405, 2012.
- V. Matys, O. V. Kel-Margoulis, E. Fricke et al., “TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes,” Nucleic Acids Research, vol. 34, database issue, pp. D108–D110, 2006.
- D. Karolchik, R. Baertsch, M. Diekhans et al., “The UCSC genome browser database,” Nucleic Acids Research, vol. 31, no. 1, pp. 51–54, 2003.
- P. Alexiou, T. Vergoulis, M. Gleditzsch et al., “miRGen 2.0: a database of microRNA genomic information and regulation,” Nucleic Acids Research, vol. 38, supplement 1, pp. D137–D141, 2010.
- F. Xiao, Z. Zuo, G. Cai, S. Kang, X. Gao, and T. Li, “miRecords: an integrated resource for microRNA-target interactions,” Nucleic Acids Research, vol. 37, supplement 1, pp. D105–D110, 2009.
- S.-D. Hsu, F.-M. Lin, W.-Y. Wu et al., “miRTarBase: a database curates experimentally validated microRNA-target interactions,” Nucleic Acids Research, vol. 39, supplement 1, pp. D163–D169, 2011.
- P. Sethupathy, B. Corda, and A. G. Hatzigeorgiou, “TarBase: a comprehensive database of experimentally supported animal microRNA targets,” RNA, vol. 12, no. 2, pp. 192–197, 2006.
- H. Dweep, C. Sticht, P. Pandey, and N. Gretz, “miRWalk—database: prediction of possible miRNA binding sites by “walking” the genes of three genomes,” Journal of Biomedical Informatics, vol. 44, no. 5, pp. 839–847, 2011.
- T. S. Keshava Prasad, R. Goel, K. Kandasamy et al., “Human protein reference database—2009 update,” Nucleic Acids Research, vol. 37, supplement 1, pp. D767–D772, 2009.
- D. Szklarczyk, A. Franceschini, M. Kuhn et al., “The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored,” Nucleic Acids Research, vol. 39, supplement 1, pp. D561–D568, 2011.
- D. Croft, G. O'Kelly, G. Wu et al., “Reactome: a database of reactions, pathways and biological processes,” Nucleic Acids Research, vol. 39, supplement 1, pp. D691–D697, 2011.
- N. le Novère, M. Hucka, H. Mi et al., “The systems biology graphical notation,” Nature Biotechnology, vol. 27, no. 8, pp. 735–741, 2009.
- A. Funahashi, Y. Matsuoka, A. Jouraku, M. Morohashi, N. Kikuchi, and H. Kitano, “CellDesigner 3.5: a versatile modeling tool for biochemical networks,” Proceedings of the IEEE, vol. 96, no. 8, pp. 1254–1265, 2008.
- M. S. Cline, M. Smoot, E. Cerami et al., “Integration of biological networks and gene expression data using Cytoscape,” Nature Protocols, vol. 2, no. 10, pp. 2366–2382, 2007.
- D.-H. Le and Y.-K. Kwon, “NetDS: a Cytoscape plugin to analyze the robustness of dynamics and feedforward/feedback loop structures of biological networks,” Bioinformatics, vol. 27, no. 19, pp. 2767–2768, 2011.
- E. O. Voit, Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists, Cambridge University Press, Cambridge, UK, 2000.
- S. Wu, S. Huang, J. Ding et al., “Multiple microRNAs modulate p21Cip1/Waf1 expression by directly targeting its 3′ untranslated region,” Oncogene, vol. 29, no. 15, pp. 2302–2308, 2010.
- P. Sætrom, B. S. E. Heale, O. Snøve Jr., L. Aagaard, J. Alluin, and J. J. Rossi, “Distance constraints between microRNA target sites dictate efficacy and cooperativity,” Nucleic Acids Research, vol. 35, no. 7, pp. 2333–2342, 2007.
- Y.-S. Jung, Y. Qian, and X. Chen, “Examination of the expanding pathways for the regulation of p21 expression and activity,” Cellular Signalling, vol. 22, no. 7, pp. 1003–1012, 2010.
- W. Wang, H. Furneaux, H. Cheng et al., “HuR regulates p21 mRNA stabilization by UV light,” Molecular and Cellular Biology, vol. 20, no. 3, pp. 760–769, 2000.
- U. Wittig, R. Kania, M. Golebiewski et al., “SABIO-RK—database for biochemical reaction kinetics,” Nucleic Acids Research, vol. 40, database issue, pp. D790–D796, 2012.
- R. Milo, P. Jorgensen, U. Moran, G. Weber, and M. Springer, “BioNumbers—the database of key numbers in molecular and cell biology,” Nucleic Acids Research, vol. 38, supplement 1, pp. D750–D753, 2010.
- I.-C. Chou and E. O. Voit, “Recent developments in parameter estimation and structure identification of biochemical and genomic systems,” Mathematical Biosciences, vol. 219, no. 2, pp. 57–83, 2009.
- A. Saltelli, K. Chan, and E. M. Scott, Sensitivity Analysis, John Wiley & Sons, New York, NY, USA, 1st edition, 2000.
- S. Strogatz, Nonlinear Dynamics and Chaos: Applications to Physics, Biology, Chemistry, and Engineering: With Applications to Physics, Biology, Chemistry and Engineering, Westview Press, Boulder, Colo, USA, 2000.
- P. Zhou, S. Cai, Z. Liu, and R. Wang, “Mechanisms generating bistability and oscillations in microRNA-mediated motifs,” Physical Review E, vol. 85, no. 4, apart 1, Article ID 041916, 9 pages, 2012.
- S. Marino, I. B. Hogue, C. J. Ray, and D. E. Kirschner, “A methodology for performing global uncertainty and sensitivity analysis in systems biology,” Journal of Theoretical Biology, vol. 254, no. 1, pp. 178–196, 2008.
- L. P. Lim, N. C. Lau, P. Garrett-Engele et al., “Microarray analysis shows that some microRNAs downregulate large numbers of-target mRNAs,” Nature, vol. 433, no. 7027, pp. 769–773, 2005.
- J. Krützfeldt, N. Rajewsky, R. Braich et al., “Silencing of microRNAs in vivo with ‘antagomirs’,” Nature, vol. 438, no. 7068, pp. 685–689, 2005.
- M. W. Pfaffl, G. W. Horgan, and L. Dempfle, “Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR,” Nucleic Acids Research, vol. 30, no. 9, p. e36, 2002.
- D. P. Bartel, “MicroRNAs: target recognition and regulatory functions,” Cell, vol. 136, no. 2, pp. 215–233, 2009.
- T. Abbas and A. Dutta, “p21 in cancer: intricate networks and multiple activities,” Nature Reviews Cancer, vol. 9, no. 6, pp. 400–414, 2009.
- J. Wang, M. Lu, C. Qiu, and Q. Cui, “TransmiR: a transcription factor microRNA regulation database,” Nucleic Acids Research, vol. 38, supplement 1, pp. D119–D122, 2010.
- S. Bandyopadhyay and M. Bhattacharyya, “PuTmiR: a database for extracting neighboring transcription factors of human microRNAs,” BMC Bioinformatics, vol. 11, article 190, 2010.
- A. Le Béchec, E. Portales-Casamar, G. Vetter et al., “MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model,” BMC Bioinformatics, vol. 12, article 67, 2011.
- M. Ashburner, C. A. Ball, J. A. Blake et al., “Gene ontology: tool for the unification of biology. The Gene Ontology Consortium,” Nature Genetics, vol. 25, no. 1, pp. 25–29, 2000.
- A. I. F. Vaz and L. N. Vicente, “A particle swarm pattern search method for bound constrained global optimization,” Journal of Global Optimization, vol. 39, no. 2, pp. 197–219, 2007.
- W. H. Press, Numerical Recipes: The Art of Scientific Computing, Cambridge University Press, Cambridge, UK, 2007.
- J. G. Doench and P. A. Sharp, “Specificity of microRNA target selection in translational repression,” Genes and Development, vol. 18, no. 5, pp. 504–511, 2004.
- B. Kholodenko, M. B. Yaffe, and W. Kolch, “Computational approaches for analyzing information flow in biological networks,” Science Signaling, vol. 5, no. 220, 2012.
- F. M. Khan, U. Schmitz, S. Nikolov et al., “Hybrid modeling of the crosstalk between signaling and transcriptional networks using ordinary differential equations and multi-valued logic,” Biochimica et Biophysica Acta, 2013.