Logic-based models for the analysis of cell signaling networks

Biochemistry

Volumn 49, Issue 15, 2010, Pages 3216-3224

  Morris, Melody K ^a   Saez Rodriguez, Julio ^a,b   Sorger, Peter K ^a,b   Lauffenburger, Douglas A ^a  

^a Massachusetts Institute of Technology   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIO-MOLECULAR; BIOCHEMICAL NETWORK; CELL SIGNALING; COMPUTATIONAL MODEL; IN-CELL; LOGIC-BASED MODELING; LOGIC-BASED MODELS; MAMMALIAN CELLS; SIGNALING NETWORKS; SIGNALING STATE; TRAINING PROCEDURES;

BIOCHEMISTRY; COMPLEXATION; CYTOLOGY; MAMMALS;

SIGNALING;

LOGIC; MAMMAL CELL; MATHEMATICAL MODEL; NONHUMAN; PHENOTYPE; PRIORITY JOURNAL; REVIEW; SIGNAL TRANSDUCTION;

BIOCHEMISTRY; CELL PHYSIOLOGICAL PHENOMENA; COMPUTERS, MOLECULAR; FUZZY LOGIC; KINETICS; LOGIC; MODELS, BIOLOGICAL; MOLECULAR BIOLOGY; PROTEINS; SIGNAL TRANSDUCTION;

MAMMALIA;

EID: 77950943011     PISSN: 00062960     EISSN: 15204995     Source Type: Journal    
DOI: 10.1021/bi902202q     Document Type: Review

References (62)

1. Kestler, H. A., Wawra, C., Kracher, B., and Kuhl, M. (2008) Network modeling of signal transduction: Establishing the global view BioEssays 30, 1110 - 1125
2. Heinrichs, A., Kritikou, E., Pulverer, B., and Raftopoulou, M., Eds. (2006) Systems biology: A user's guide, Nature Publishing Group, New York.
3. Janes, K. A. and Lauffenburger, D. A. (2006) A biological approach to computational models of proteomic networks Curr. Opin. Chem. Biol. 10, 73 - 80
4. Ideker, T. and Lauffenburger, D. (2003) Building with a scaffold: Emerging strategies for high- to low-level cellular modeling Trends Biotechnol. 21, 255 - 262
5. Aldridge, B. B., Burke, J. M., Lauffenburger, D. A., and Sorger, P. K. (2006) Physicochemical modelling of cell signalling pathways Nat. Cell Biol. 8, 1195 - 1203
6. Raj, A. and van Oudenaarden, A. (2008) Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences Cell 135, 216 - 226
7. Bauer-Mehren, A., Furlong, L. I., and Sanz, F. (2009) Pathway databases and tools for their exploitation: Benefits, current limitations and challenges Mol. Syst. Biol. 5, 290
8. Rual, J., Venkatesan, K., Hao, T., Hirozane-Kishikawa, T., Dricot, A., Li, N., Berriz, G. F., Gibbons, F. D., Dreze, M., Ayivi-Guedehoussou, N., Klitgord, N., Simon, C., Boxem, M., Milstein, S., Rosenberg, J., Goldberg, D. S., Zhang, L. V., Wong, S. L., Franklin, G., Li, S., Albala, J. S., Lim, J., Fraughton, C., Llamosas, E., Cevik, S., Bex, C., Lamesch, P., Sikorski, R. S., Vandenhaute, J., Zoghbi, H. Y., Smolyar, A., Bosak, S., Sequerra, R., Doucette-Stamm, L., Cusick, M., Hill, D., Roth, F. P., and Vidal, M. (2005) Towards a proteome-scale map of the human protein-protein interaction network Nature 437, 1173 - 1178
9. Joughin, B. A., Cheung, E., Karuturi, R., Saez-Rodriguez, J., Lauffenburger, D. A., and Liu, E. T. (2009) Cellular Signaling Networks. In Systems Biomedicine, Concepts and Perspective (Liu, E. and Lauffenburger, D. A., Eds.) Elseveier, Amsterdam.
10. Kauffman, S. A. (1969) Metabolic stability and epigenesis in randomly constructed genetic nets J. Theor. Biol. 22, 437 - 467
11. de Jong, H. (2002) Modeling and simulation of genetic regulatory systems: A literature review J. Comput. Biol. 9, 67 - 103
12. Thomas, R. and D'Ari, R. (1990) Biological Feedback, CRC Press, Boca Raton, FL.
13. Huang, S. and Ingber, D. E. (2000) Shape-dependent control of cell growth, differentiation, and apoptosis: Switching between attractors in cell regulatory networks Exp. Cell Res. 261, 91 - 103
14. Aldridge, B., Saez-Rodriguez, J., Muhlich, J., Sorger, P., and Lauffenburger, D. A. (2009) Fuzzy logic analysis of kinase pathway crosstalk inTNF/EGF/insulin-induced signaling PLoS Comput. Biol. 5, e1000340
15. Franke, R., Muller, M., Wundrack, N., Gilles, E. D., Klamt, S., Kahne, T., and Naumann, M. (2008) Host-pathogen systems biology: Logical modeling of hepatocyte growth factor and Helicobacter pylori induced c-Met signal transduction BMC Syst. Biol. 2, 4
16. Gupta, S., Bisht, S. S., Kukreti, R., and Jain, S. (2007) Boolean network analysis of a neurotransmitter signaling pathway J. Theor. Biol. 244, 463 - 469
17. Helikar, T., Konvalina, J., Heidel, J., and Rogers, J. A. (2008) Emergent decision-making in biological signal transduction networks Proc. Natl. Acad. Sci. U.S.A. 105, 1913 - 1918
18. Huang, Z. and Hahn, J. (2009) Fuzzy modeling of signal transduction networks Chem. Eng. Sci. 64, 2044 - 2056
19. Kaufman, M., Andris, F., and Leo, O. (1999) A logical analysis of T cell activation and anergy Proc. Natl. Acad. Sci. U.S.A. 96, 3894 - 3899
20. Li, S., Assmann, S. M., and Albert, R. (2006) Predicting essential components of signal transduction networks: A dynamic model of guard cell abscisic acid signaling PLoS Biol. 4, 1732 - 1748
21. Mai, Z. and Liu, H. (2009) Boolean network-based analysis of the apoptosis network: Irreversible apoptosis and stable surviving J. Theor. Biol. 259, 760 - 769
22. Mendoza, L. (2006) A network model for the control and differentiation process in Th cells BioSystems 84, 101 - 114
23. Philippi, N., Wlter, D., Schlatter, R., Ferreira, K., Ederer, M., Sawodny, O., Timmer, J., Borner, C., and Dandekar, T. (2009) Modeling system states in liver cells: Survival, apoptosis, and their modifications in response to viral infection BMC Syst. Biol. 3, 97
24. Saez-Rodriguez, J., Simeoni, L., Lindquist, J. A., Hemenway, R., Bommhardt, U., Arndt, B., Haus, U. U., Weismantel, R., Gilles, E. D., Klamt, S., and Schraven, B. (2007) A logical model provides insights into T cell receptor signaling PLoS Comput. Biol. 3, e163
25. Saez-Rodriguez, J., Alexopoulos, L. G., Epperlein, J., Samaga, R., Lauffenburger, D. A., Klamt, S., and Sorger, P. (2009) Discrete logic modeling as a means to link protein signaling networks and functional analysis of mammalian signal transduction Mol. Syst. Biol. 5, 331
26. Sahin, O., Frohlich, H., Lobke, C., Korf, U., Burmester, S., Majety, M., Mattern, J., Schupp, I., Chaouiya, C., Thieffry, D., Poustka, A., Wiemann, S., Beissbarth, T., and Arlt, D. (2009) Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance BMC Syst. Biol. 3, 1
27. Samaga, R., Saez-Rodriguez, J., Alexopoulos, L. G., Sorger, P. K., and Klamt, S. (2009) The Logic of EGFR/ErbB Signaling: Theoretical Properties and Analysis of High-Throughput Data PLoS Comput. Biol. 5, e1000438
28. Wittmann, D., Krumsiek, J., Saez-Rodriguez, J., Lauffenburger, D. A., Klamt, S., and Theis, F. (2009) From Qualitative to Quantitative Modeling BMC Syst. Biol. 3, 98
29. Zhang, R., Shah, M., Yang, J., Nyland, S., Liu, X., Yun, J., Albert, R., and Loughran, T. (2008) Network model of survival signaling in large granular lymphocyte leukemia Proc. Natl. Acad. Sci. U.S.A. 105, 16308
30. Zielinski, R., Przytycki, P. F., Zheng, J., Zhang, D., Przytycka, T. M., and Capala, J. (2009) The crosstalk between EGF, IGF, and insulin cell signaling pathways: Computations and experimental analysis BMC Syst. Biol. 3, 88
31. Wu, M., Yang, X., and Chan, C. (2009) A Dynamic Analysis of IRS-PKR Signaling in Liver Cells: A Discrete Modeling Approach PLoS One 4 e8040
32. Schlatter, R., Schmich, K., Vizcarra, I. A., Scheurich, P., Sauter, T., Borner, C., Ederer, M., Merfort, I., and Sawodny, O. (2009) ON/OFF and Beyond: A Boolean Model of Apoptosis PLoS Comput. Biol. 5 e1000595
33. Mitsos, A., Melas, I., Siminelaki, P., Chairakai, A., Saez-Rodriguez, J., and Alexopoulos, L. G. (2009) Identifying Drug Effects via Pathway Alteractions usingan Interger Linear Programming Optimization Formulation on Phosphoproteomic Data PLoS Comput. Biol. 5 e1000591
34. Thomas, R. and Kaufman, M. (2001) Multistationarity, the basis of cell differentiation and memory. I. Structural conditions of multistationarity and other nontrivial behavior Chaos 11, 170 - 179
35. Kaufman, M., Urbain, R., and Thomas, R. (1985) Towards a logical analysis of the immune response J. Theor. Biol. 114, 527 - 561
36. Thakar, J., Pilione, M., Kirimanjeswara, G., Harvill, T. T., and Albert, R. (2007) Modeling systems-level regulation of host immune responses PLoS Comput. Biol. 3, e109
37. Glass, L. and Kauffman, S. A. (1973) The Logical Analysis of Continuous, Non-linear Biochemical Control Networks J. Theor. Biol. 39, 103 - 129
38. Mendoza, L. and Xenarios, I. (2006) A method for the generation of standardized qualitative dynamical systems of regulatory networks Theor. Biol. Med. Modell. 3, 13
39. Thomas, R. (1973) Boolean formalization of genetic control circuits J. Theor. Biol. 42, 563 - 585
40. Garg, A., Di Cara, A., Xenarios, I., Mendoza, L., and De Micheli, G. (2008) Synchronous versus asynchronous modeling of gene regulatory networks Bioinformatics 24, 1917 - 1925
41. Klamt, S., Saez-Rodriguez, J., Lindquist, J., Simeoni, L., and Gilles, E. D. (2006) A Methodology for the Structural and Functional Analysis of Signaling and Regulatory Networks BMC Bioinf. 7, 56
42. Chaves, M., Sontag, E. D., and Albert, R. (2006) Methods of robustness analysis for Boolean models of gene control networks IEEE Proc. Syst. Biol. 153, 154 - 167
43. Fauré, A., Naldi, A., Chaouiya, C., and Thieffry, D. (2006) Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle Bioinformatics 22, e124 - e131
44. Shmulevich, I., Dougherty, E. R., Kim, S., and Zhang, W. (2002) Probabilistic Boolean Networks: A rule-based uncertainty model for gene regulatory networks Bioinformatics 18, 261 - 274 (Pubitemid 34183104)
45. Gat-Viks, I. and Shamir, R. (2007) Refinement and expansion of signaling pathways: The osmotic response network in yeast Genome Res. 17, 358 - 367
46. Fisher, J. and Henzinger, T. (2007) Executable cell biology Nat. Biotechnol. 25, 1239 - 1249
47. Abdi, A., Tahoori, M. B., and Emamian, E. S. (2008) Fault diagnosis Engineering of Digital Circuits Can Identify Vulnerable Molecules in Complex Cellular Pathways Sci. Signal. 1, ra10
48. Oda, K., Matsuoka, Y., Funahashi, A., and Kitano, H. (2005) A comprehensive pathway map of epidermal growth factor receptor signaling Mol. Syst. Biol. 1 2005 0010
49. Saez-Rodriguez, J., Mirschel, S., Hemenway, R., Klamt, S., Gilles, E. D., and Ginkel, M. (2006) Visual setup of logical models of signaling and regulatory networks with ProMoT BMC Bioinf. 7, 506
50. Klamt, S., Saez-Rodriguez, J., and Gilles, E. D. (2007) Structural and functional analysis of cellular networks with CellNetAnalyzer BMC Syst. Biol. 1, 2
51. Li, F., Long, T., Lu, Y., Ouyang, Q., and Tang, C. (2004) The yeast cell-cycle network is robustly designed Proc. Natl. Acad. Sci. U.S.A. 101, 4781 - 4786
52. Davidich, M. I. and Bornholdt, S. (2008) Boolean network model predicts cell cycle sequence of fission yeast PLoS One 3, e1672
53. Mendoza, L. and Alvarez-Buylla, E. R. (1998) Dynamics of the genetic regulatory netowrk for Arabidopsis thaliana flower morphogenesis J. Theor. Biol. 193, 307 - 319
54. Mendoza, L., Thieffry, D., and Alvarez-Buylla, E. R. (1999) Genetic control of flower morphogenesis in Arabidopsis thaliana: A logical analysis Bioinformatics 15, 593 - 606 (Pubitemid 29462108)
55. Braunewell, S. and Bornholdt, S. (2007) Superstability of the yeast cell-cycle dynamics: Ensuring causality in the presence of biochemical stochasticity J. Theor. Biol. 245, 638 - 643 (Pubitemid 46452662)
56. Albert, I., Thakar, J., Li, S., Zhang, R., and Albert, R. (2008) Boolean network simulations for life scientists Source Code Biol. Med. 3, 16
57. Chaouiya, C., Remy, E., Mosse, B., and Thieffry, D. (2003) Qualitative Analysis of Regulatory Graphs: A Computations Tool Based On a Discrete Formal Framework. In Lecture Notes in Control and Information Sciences, Positive Systems (Benvenuit, L., De Santis, A., and Farina, L., Eds.) pp 119 - 126, Springer-Verlag, Berlin.
58. Gonzalez, A. G., Naldi, A., Sanchez, L., Thieffry, D., and Chaouiya, C. (2006) GINsim: A software suite for the qualitative modelling, simulation, and analysis of regulatory networks BioSystems 84, 91 - 100 (Pubitemid 43670490)
59. de Jong, H., Geiselmann, J., Hernandez, C., and Page, M. (2003) Genetic Network Analyzer: Qualitative simulation of genetic regulatory networks Bioinformatics 19, 336 - 344 (Pubitemid 36284933)
60. Helikar, T. and Rogers, J. A. (2009) ChemChains: A platform for simulation and analysis of biochemical networks aimed to laboratory scientists BMC Syst. Biol. 3, 58
61. Ulitsky, I., Gat-Viks, I., and Shamir, R. (2008) MetaReg: A platform for modeling, analysis, and visualization of biological systems using large-scale experimental data Genome Biol. 9, R1
62. DiCara, A., Garg, A., DeMicheli, B., Xenarios, I., and Mendoza, L. (2007) Dynamic simulation of regulatory networks using SQUAD BMC Bioinf. 8, 462 (Pubitemid 351228650)