Gene regulatory network modeling using literature curated and high throughput data

Systems and Synthetic Biology

Volumn 6, Issue 3-4, 2012, Pages 69-77

  Kulkarni, Vishwesh V ^a   Arastoo, Reza ^b   Bhat, Anupama ^c   Subramanian, Kalyansundaram ^c   Kothare, Mayuresh V ^b   Riedel, Marc C ^a  

^a University of Minnesota   (United States)

^b Lehigh University   (United States)

^c Strand Life Sciences ^*  (India)

Author keywords

Convex optimization; Gene regulatory networks; High throughput data; Linear matrix inequalities; Linear models; Ordinary differential equations

Indexed keywords

EID: 84871412941     PISSN: 18725325     EISSN: 18725333     Source Type: Journal    
DOI: 10.1007/s11693-012-9100-4     Document Type: Article

References (20)

1. Apkarian P, Becker G, Gahinet P, Kajiwara H (1996) LMI techniques in control engineering from theory to practice. In: Workshop notes-IEEE conference on decision and control, Kobe, Japan.
2. Arnone M, Davidson E (1997) The hardwiring of development: organization and function of genomic regulatory systems. Development 124: 1851-1864.
3. Bansal M, Belcastro V, Ambesi-Impiombato A, di Bernardo D (2007) How to infer gene networks from expression profiles. Mol Syst Biol 3(78). doi: 10. 1038/msb4100120.
4. Bansal M, Gatta G, di Bernardo D (2006) Inference of gene regulatory networks and compound mode of action from time course gene expression profiles. Bioinformatics 22(7): 815-822. doi: 10. 1093/bioinformatics/btl003. http://bioinformatics. oxfordjournals. org/content/22/7/815. full.
5. Boyd S, Vandenberghe L (2003) Convex optimization. Cambridge University Press, Cambridge.
6. Desoer C, Vidyasagar M (1975) Feedback systems: input-output properties. Academic Press, New York.
7. DiBernardo D, Gardner TS, Collins JJ (2004) Robust identification of large scale genetic networks. In: Altman RB, Dunker AK, Hunter L, Jung TA, Klein TE (eds) Biocomputing 2004, proceedings of the Pacific symposium, Hawaii, USA, 6-10 January 2004, World Scientific, pp 486-497.
8. Gardner TS, di Bernardo D, Lorenz D, Collins JJ (2003) Inferring genetic networks and identifying compound mode of action via expression profiling. Science 301: 102-105.
9. Horn R, Johnson C (1991) Topics in matrix analysis. Cambridge University Press, Cambridge.
10. Mees A (1981) Achieving diagonal dominance. Syst Cont Lett 1(3): 155-158.
11. Penfold C, Wild D (2011) How to infer gene networks from expression profiles, revisited. Interface Focus Online 1(3): 857-870. doi: 10. 1098/rsfs. 2011. 0053.
12. Sastry S (1999) Nonlinear systems-analysis, stability and control. Springer, New York.
13. Smoot M, Ono K, Ruscheinski J, Wang P, Ideker T (2011) Cytoscape 2. 8: new features for data integration and network visualization. Bioinformatics 27(3): 431-432. doi: 10. 1093/bioinformatics/btq675.
14. Sontag E (2008) Network reconstruction based on steady-state data. Essays Biochem 45: 161-176.
15. Sontag E, Kiyatkin A, Kholodenko B (2004) Inferring dynamic architecture of cellular networks using time-series of gene expression, protein and metabolite data. BMC Bioinform 20(12): 1877-1886.
16. Tegner J, Yeung M, Hasty J, Collins JJ (2003) Reverse engineering gene networks: integrating genetic perturbations with dynamical modeling. PNAS 100(10): 5944-5949. doi: 10. 1073/pnas. 0933416100. http://www. pnas. org/content/100/10/5944. full.
17. Theiffry D, Huerta A, Perez-Rueda E, Collado-Vides J (1998) From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli. Bioessays 20(5): 433-440.
18. Vidyasagar M (1993) Nonlinear systems analysis (second edition). Prentice-Hall, Englewood Cliffs, N. J.
19. Yuan Y, Stan G, Warnick S, Goncalves J (2010) Robust dynamical network reconstruction. In: IEEE conference on decision and control. Atlanta, pp 180-185.
20. Zavlanos M, Julius A, Boyd S, Pappas G (2011) Inferring stable genetic networks from steady-state data. Automatica: Special Issue Syst Biol 47(6): 1113-1122.