Integration of Boolean models exemplified on hepatocyte signal transduction

Briefings in Bioinformatics

Volumn 13, Issue 3, 2012, Pages 365-376

  Schlatter, Rebekka ^a   Philippi, Nicole ^b   Wangorsch, Gaby ^b   Pick, Robert ^c   Sawodny, Oliver ^a   Borner, Christoph ^d   Timmer, Jens ^d   Ederer, Michael ^a   Dandekar, Thomas ^b  

^a UNIVERSITY OF STUTTGART   (Germany)

^b UNIVERSITY OF WÜRZBURG   (Germany)

^c LUDWIG MAXIMILIANS UNIVERSITY   (Germany)

^d UNIVERSITY OF FREIBURG   (Germany)

Author keywords

Apoptosis; Boolean modelling; Model integration; Pathway

Indexed keywords

APOPTOSIS; ARTICLE; LIVER; LIVER CELL; METABOLISM; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; THEORETICAL MODEL;

APOPTOSIS; HEPATOCYTES; LIVER; MODELS, THEORETICAL; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY;

EID: 84861817796     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbr065     Document Type: Article

References (38)

1. Damiani C, Serra R, Villani M, et al. Cell-cell interaction and diversity of emergent behaviours. IETSyst Biol 2011;5: 137.
2. Millat T, Wolkenhauer O, Fischer RJ, et al. Modeling of cellular processes: methods, data, and requirements. Methods Mol Biol 2011;696:429-37.
3. Voit EO. Modelling metabolic networks using power-laws and S-systems. Essays Biochem 2008;45:29-40.
4. Schlatter R, Schmich K, Avalos Vizcarra I, et al. ON/OFF and Beyond - a Boolean model of apoptosis. PLoSComput Biol 2009;5:e1000595.
5. Philippi N, Walter D, Schlatter R, et al. Modeling system states in liver cells: survival, apoptosis and their modifications in response to viral infection. BMC Syst Biol 2009; 3:97.
6. Samaga R, Saez-Rodriguez J, Alexopoulos LG, et al. The logic of EGFR/ErbB signalling: theoretical properties and analysis of high-throughput data. PLoSComput Biol 2009;5: e1000438.
7. Thakar J, Albert R. Boolean models of within-host immune interactions. Curr Opin Microbiol 2010;13(3):377-81.
8. Balleza E, Alvarez-Buylla ER, Chaos A, et al. Critical dynamics in genetic regulatory networks: examples from four kingdoms. PLoS One 2008;3(6):e2456.
9. Alvarez-Buylla ER, Chaos A, Aldana M, et al. Floral morphogenesis: stochastic explorations of a gene network epigenetic landscape. PLoS One 2008;3(11):e3626.
10. Saez-Rodriguez J, Alexopoulos LG, Zhang M, et al. Comparing signaling networks between normal and transformed hepatocytes using discrete logical models. Cancer Res 2011;71(16):5400-11.
11. Morris MK, Saez-Rodriguez J, Clarke DC, et al. Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli. PLoS Comput Biol 2011; 7(3):e1001099.
12. Garg A, Di Cara A, Xenarious I, et al. Synchronous versus asynchronous modelling of gene regulatory networks. Bioinformatics 2008;24(17):1917-25.
13. Wittmann DM, Krumsiek J, Saez-Rodriguez J, et al. Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling. BMCSyst Biol 2009;3:98.
14. Wang RS, Albert R. Elementary signaling modes predict the essentiality of signal transduction network components. BMCSyst Biol 2011;5:44.
15. Chaves M, Tournier L, Gouzé JL. Comparing Boolean and piecewise affine differential models for genetic networks. Acta Biotheor 2010;58(2-3):217-32.
16. Giacomantonio CE, Goodhill GJ. A Boolean model of the gene regulatory network underlying Mammalian cortical area development. PLoSComput Biol 2010;6(9):e1000936.
17. Veliz-Cuba A, Stigler B. Boolean models can explain bistability in the lac operon. JComput Biol 2011;18:783-94.
18. Wang H, Lu HH, Chueh TH. Constructing biological pathways by a two-step counting approach. PLoS One 2011;6:e20074.
19. Jack J, Wambaugh JF, Shah I. Simulating quantitative cellular responses using asynchronous threshold Boolean network ensembles. BMCSyst Biol 2011;5:109.
20. De Jong H, Geiselmann J, Hernandez C, et al. Genetic Network Analyzer: qualitative simulation of genetic regulatory networks. Bioinformatics 2003;19(3):336-44.
21. Müssel C, Hopfensitz M, Kestler HA. BoolNet-an R package for generation, reconstruction and analysis of Boolean networks. Bioinformatics 2010;26(10):1378-80.
22. Albert I, Thakar J, Li S, et al. Boolean network simulations for life scientists. SourceCode BiolMed 2008;3:16.
23. Naldi A, Berenguier D, Fauré A, et al. Logical modelling of regulatory networks with GINsim 2.3. Biosystems 2009; 97(2):134-9.
24. Sneddon MW, Faeder JR, Emonet T. Efficient modeling, simulation and coarse-graining of biological complexity with NFsim. NatMethods 2011;8(2):177-83.
25. Di Cara A, Garg A, De Micheli G, etal. Dynamic simulation of regulatory networks using SQUAD. BMC Bioinformatics 2007;8:462.
26. Klamt SJ, Saez-Rodriguez JA, Lindquist L, et al. A methodology for the structural and functional analysis of signalling and regulatory networks. BMC Bioinformatics 2006;7:56.
27. Schlatter R, Knies D, Ederer M, et al. Analysis of Boolean Models using quality assurance methods from software engineering. IEEE Multi-Conference on Systems and Control (MSC), Yokohama 2010.
28. Fauré A, Naldi A, Chaouiya C, et al. Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle. BMC Bioinformatics 2006;22:e124-31.
29. Maiwald T, Timmer J. Dynamical modeling and multiexperiment fitting with PottersWheel. Bioinformatics 2008; 24:2037-43.
30. Krumsiek J, Pölsterl S, Wittmann DM, et al. Odefy-from discrete to continuous models. BMC Bioinformatics 2010;11: 233.
31. Wittmann DM, Krumsiek J, Saez-Rodriguez J, et al. Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling. BMCSyst Biol 2009;3:98.
32. Kühnel M, Mayorga LS, Dandekar T, et al. Modelling phagosomal lipid networks that regulate actin assembly. BMCSyst Biol 2008;2:107.
33. Li C, Nagasaki M, Koh CH, et al. Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension. Mol Biosyst 2011;7:1576-92.
34. Bentele M, Lavrik I, Ulrich M, et al. Mathematical modelling reveals threshold mechanism in CD95-induced apoptosis. JCell Biol 2004;166:839-51.
35. Walter D, Schmich K, Vogel S, et al. Switch from type II to I Fas/CD95 death signaling on in vitro culturing of primary hepatocytes. Hepatology 2009;48:1942-53.
36. Schmich K, Schlatter R, Corazza N, et al. Tumor necrosis factor a sensitizes primary murine hepatocytes to Fas/ CD95-induced apoptosis in a Bim- and Bid-dependent manner. Hepatology 2011;53:282-92.
37. Zhang Q, Liang C, Yu YA, et al. The highly attenuated oncolytic recombinant vaccinia virus GLV-1h68: comparative genomic features and the contribution of F14.5L inactivation. Mol Genet Genomics 2009;282:417-35.
38. Schanz J, Pusch J, Hansmann J, et al. Vascularised human tissue models: a new approach for the refinement of biomedical research. J Biotechnol 2010;148:56-63.