ENISI SDE: A new web-based tool for modeling stochastic processe

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 12, Issue 2, 2015, Pages 289-297

  Mei, Yongguo ^a   Carbo, Adria ^a   Hoops, Stefan ^a   Hontecillas, Raquel ^a   Bassaganya Riera, Josep ^a  

^a VIRGINIA BIOINFORMATICS INSTITUTE   (United States)

Author keywords

Computational biology; Differential equations; Modeling; Modeling tools; Simulations; Stochastic differential equations; Stochastic modeling; Web interface

Indexed keywords

BIOINFORMATICS; BIOLOGY; DIFFERENTIAL EQUATIONS; IMMUNOLOGY; MODELS; ORDINARY DIFFERENTIAL EQUATIONS; RANDOM PROCESSES; SOCIAL NETWORKING (ONLINE); STOCHASTIC MODELS; T-CELLS; USER INTERFACES; WEBSITES;

COMPUTATIONAL BIOLOGY; MODELING TOOL; SIMULATIONS; STOCHASTIC DIFFERENTIAL EQUATIONS; WEB INTERFACE;

STOCHASTIC SYSTEMS;

ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; CELL DIFFERENTIATION; COMPUTER PROGRAM; CYTOLOGY; HUMAN; INTERNET; MARKOV CHAIN; PROCEDURES; T LYMPHOCYTE;

ALGORITHMS; CELL DIFFERENTIATION; COMPUTATIONAL BIOLOGY; HUMANS; INTERNET; MODELS, BIOLOGICAL; SOFTWARE; STOCHASTIC PROCESSES; T-LYMPHOCYTES;

EID: 84927670020     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2014.2351823     Document Type: Article

References (49)

1. S. Adra, T. Sun, S. MacNeil, M. Holcombe, and R. Smallwood, "Development of a three dimensional multiscale computational model of the human epidermis," PLoS One, vol. 5, no. 1, p. e8511, 2010.
2. K. Arnold, L. Bordoli, J. Kopp, and T. Schwede, "The swiss-model workspace:Aweb-based environment for protein structure homology modelling," Bioinformatics, vol. 22, no. 2, pp. 195-201, 2006.
3. E. Bettelli, Y. Carrier, W. Gao, T. Korn, T. B. Strom, M. Oukka, H. L. Weiner, and V. K. Kuchroo, "Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells," Nature, vol. 441, no. 7090, pp. 235-238, May 2006.
4. E. Borenstein, "Computational systems biology and in silico modeling of the human microbiome," Brief Bioinform., vol. 13, no. 6, p. 769, May 2012.
5. X. Cai, and J. Wen, "Efficient exact and K-skip methods for stochastic simulation of coupled chemical reactions," J. Chem. Phys., vol. 131, no. 6, p. 064108, Aug. 2009.
6. Y. Cao, D. T. Gillespie, and L. R. Petzold, "The slow-scale stochastic simulation algorithm," J. Chem. Phys., vol. 122, no. 1, p. 14116, Jan. 2005.
7. A. Carbo, J. Bassaganya-Riera, M. Pedragosa, M. Viladomiu, M. Marathe, S. Eubank, K. Wendelsdorf, K. Bisset, S. Hoops, X. Deng, M. Alam, B. Kronsteiner, Y. Mei, and R. Hontecillas, "Predictive computational modeling of the mucosal immune responses during helicobacter pylori infection," PloS One, vol. 8, no. 9, p. e73365, 2013.
8. A. Carbo, R. Hontecillas, B. Kronsteiner, M. Viladomiu, M. Pedragosa, P. Lu, C. W. Philipson, S. Hoops, M. Marathe, S. Eubank, K. Bisset, K. Wendelsdorf, A. Jarrah, Y. Mei, and J. Bassaganya- Riera, "Systems modeling of molecular mechanisms controlling cytokine-driven cd4+ t cell differentiation and phenotype plasticity," PLoS Comput. Biol., vol. 9, no. 4, p. e1003027, 2013.
9. K. C. Chen, T. Y. Wang, H. H. Tseng, C. Y. Huang, and C. Y. Kao, "A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae," Bioinformatics, vol. 21, no. 12, pp. 2883-2890, Jun. 2005.
10. Z. Chen, F. Lin, Y. Gao, Z. Li, J. Zhang, Y. Xing, Z. Deng, Z. Yao, A. Tsun, and B. Li, "Foxp3 and rorgt: Transcriptional regulation of treg and th17," Int. Immunopharmacology, vol. 11, no. 5, pp. 536-542, 2011.
11. H. de Jong, "Modeling and simulation of genetic regulatory systems: A literature review," J. Comput. Biol., vol. 9, no. 1, pp. 67-103, 2002.
12. C. DeLisi, "Mathematical modeling in immunology," Annu. Rev. Biophys. Bioeng., vol. 12, pp. 117-138, 1983.
13. S. Forrest and C. Beauchemin, "Computer immunology," Immunological Rev., vol. 216, pp. 176-197, 2007.
14. D. T. Gillespie, "A general method for numerically simulating the stochastic time evolution of coupled chemical reactions," J. Comput. Physics., vol. 22, no. 4, pp. 403-434, 1976.
15. D. T. Gillespie, "Exact stochastic simulation of coupled chemical reactions," J. Phys. Chem., vol. 81, no. 25, pp. 2340-2361, 1977.
16. J. Goecks, A. Nekrutenko, J. Taylor, and Galaxy Team, "Galaxy: A comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences," Genome Biol., vol. 11, no. 8, p. R86, 2010.
17. N. S. Goel and N. Richter-Dyn, Stochastic Models in Biology. San Francisco, CA, USA: Academic, 1974.
18. H. J. Gold, Mathematical Modeling of Biological Systems: An Introductory Guidebook. New York, NY, USA: Wiley, 1977.
19. M. Holcombe, S. Adra, M. Bicak, S. Chin, S. Coakley, A. I. Graham, J. Green, C. Greenough, D. Jackson, M. Kiran, S. Mac- Neil, A. Maleki-Dizaji, P. McMinn, M. Pogson, R. Poole, E. Qwarnstrom, F. Ratnieks, M. D. Rolfe, R. Smallwood, T. Sun, and D. Worth, "Modelling complex biological systems using an agentbased approach," Integr. Biol., vol. 4, no. 1, pp. 53-64, Jan. 2012.
20. S. Hoops, S. Sahle, R. Gauges, C. Lee, J. Pahle, N. Simus, M. Singhal, L. Xu, P. Mendes, and U. Kummer, "COPASI - A complex pathway simulator," Bioinformatics, vol. 22, no. 24, pp. 3067-3074, Dec. 2006.
21. M. Hucka, A. Finney, H. M. Sauro, H. Bolouri, J. C. Doyle, H. Kitano, A. P. Arkin, B. J. Bornstein, D. Bray, A. Cornish-Bowden, A. A. Cuellar, S. Dronov, E. D. Gilles, M. Ginkel, V. Gor, I. I. Goryanin, W. J. Hedley, T. C. Hodgman, J. H. Hofmeyr, P. J. Hunter, N. S. Juty, J. L. Kasberger, A. Kremling, U. Kummer, N. Le Novere, L. M. Loew, D. Lucio, P. Mendes, E. Minch, E. D. Mjolsness, Y. Nakayama, M. R. Nelson, P. F. Nielsen, T. Sakurada, J. C. Schaff, B. E. Shapiro, T. S. Shimizu, H. D. Spence, J. Stelling, K. Takahashi, M. Tomita, J. Wagner, and J. Wang, "The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models," Bioinformatics, vol. 19, no. 4, pp. 524-531, Mar. 2003.
22. S. M. Iacus, Simulation and Inference for Stochastic Differential Equations: With R Examples(Springer Series in Statistics), 1st ed. New York, NY, USA: Springer, 2008.
23. F. H. Karlsson, I. Nookaew, D. Petranovic, and J. Nielsen, "Prospects for systems biology and modeling of the gut microbiome," Trends Biotechnol., vol. 29, no. 6, pp. 251-258, Jun. 2011.
24. H. Kitano, "Computational systems biology," Nature, vol. 420, no. 6912, pp. 206-210, Nov. 2002.
25. P. E. Kloeden, and E. Platen, Numerical Solution of Stochastic Differential Equations, vol. 23. New York, NY, USA: Springer, 1992.
26. N. Le Novere, and T. S. Shimizu, "STOCHSIM: Modelling of stochastic biomolecular processes," Bioinformatics, vol. 17, no. 6, pp. 575-576, Jun. 2001.
27. Z. Liu, and Y. Cao, "Detailed comparison between StochSim and SSA," IET Syst. Biol., vol. 2, no. 5, pp. 334-341, Sep. 2008.
28. B. D. Macarthur, A. Ma'ayan, and I. R. Lemischka, "Systems biology of stem cell fate and cellular reprogramming," Nat. Rev. Mol. Cell Biol., vol. 10, no. 10, pp. 672-681, Oct. 2009.
29. B. D. MacArthur, C. P. Please, and R. O. Oreffo, "Stochasticity and the molecular mechanisms of induced pluripotency," PLoS One, vol. 3, no. 8, p. e3086, 2008.
30. T. Manninen, M. L. Linne, and K. Ruohonen, "Developing It stochastic differential equation models for neuronal signal transduction pathways," Comput. Biol. Chem., vol. 30, no. 4, pp. 280-291, Aug. 2006.
31. Y. Mei, A. Carbo, R. Hontecillas, and J. Bassaganya-Riera, "Enisi SDE: A novel web-based stochastic modeling tool for computational biology," in Proc. IEEE Int. Conf. Bioinformat. Biomed., Dec. 2013, pp. 392-397.
32. Y. Mei, R. Hontecillas, X. Zhang, K. Bisset, S. Eubank, S. Hoops, M. Marathe, and J. Bassaganya-Riera, "Enisi visual, an agentbased simulator for modeling gut immunity," in Proc. IEEE Int. Conf. Bioinformat. Biomed., Oct. 2012, pp. 1-5.
33. M. Meier-Schellersheim, I. D. Fraser, and F. Klauschen, "Multiscale modeling for biologists," Wiley Interdisciplinary Rev.: Syst. Biol. Med., vol. 1, no. 1, pp. 4-14, 2009.
34. J. A. Morgan and D. Rhodes, "Mathematical modeling of plantmetabolic pathways," Metabolic Eng., vol. 4, no. 1, pp. 80-89, Jan. 2002.
35. B. Novak, Z. Pataki, A. Ciliberto, and J. J. Tyson, "Mathematical model of the cell division cycle of fission yeast," Chaos, vol. 11, no. 1, pp. 277-286, Mar. 2001.
36. B. Novak and J. J. Tyson, "Modeling the control of DNA replication in fission yeast," Proc. Nat. Acad. Sci. USA, vol. 94, no. 17, pp. 9147-9152, Aug. 1997.
37. H. V. D. Parunak, R. Savit, and R. L. Riolo, "Agent-based modeling vs. equation-based modeling: A case study and users guide," in Multi-Agent Systems and Agent-Based Simulation. New York, NY, USA: Springer, 1998, pp. 10-25.
38. L. Petzold and A. Hindmarsh, "LSODA (Livermore solver of ordinary differential equations)," Comput. Math. Res. Division, Lawrence Livermore Nat. Laboratory, Livermore, CA, USA, 1997.
39. D. Posada, "Modeltest server: A web-based tool for the statistical selection of models of nucleotide substitution online," Nucl. Acids Res., vol. 34, no. suppl 2, pp. W700-W703, 2006.
40. R. Ramaswamy and I. F. Sbalzarini, "A partial-propensity formulation of the stochastic simulation algorithm for chemical reaction networks with delays," J. Chem. Phys., vol. 134, no. 1, p. 014106, Jan. 2011.
41. A. Saarinen, M. L. Linne, and O. Yli-Harja, "Stochastic differential equation model for cerebellar granule cell excitability," PLoS Comput. Biol., vol. 4, no. 2, p. e1000004, Feb. 2008.
42. E. Schneidman, B. Freedman, and I. Segev, "ION channel stochasticity may be critical in determining the reliability and precision of spike timing," Neural Comput., vol. 10, no. 7, pp. 1679-1703, Oct. 1998.
43. SDE-Matlab-Toolbox [Online]. Available: http://sdetoolbox. sourceforge.net/, 2007.
44. A. A. Sharov, D. B. Dudekula, and M. S. Ko, "A web-based tool for principal component and significance analysis of microarray data," Bioinformatics, vol. 21, no. 10, pp. 2548-2549, 2005.
45. X. Solé, E. Guinó, J. Valls, R. Iniesta, and V. Moreno, "Snpstats: A web tool for the analysis of association studies," Bioinformatics, vol. 22, no. 15, pp. 1928-1929, 2006.
46. D. M. Tartar, A. M. VanMorlan, X. Wan, F. B. Guloglu, R. Jain, C. L. Haymaker, J. S. Ellis, C. M. Hoeman, J. A. Cascio, M. Dhakal, M. Oukka, and H. Zaghouani, "FoxP3+RORgammat+ T helper intermediates display suppressive function against autoimmune diabetes," J. Immunol., vol. 184, no. 7, pp. 3377-3385, Apr. 2010.
47. M. Terzer, N. D. Maynard, M. W. Covert, and J. Stelling, "Genome-scale metabolic networks," Wiley Interdiscip Rev. Syst. Biol. Med., vol. 1, no. 3, pp. 285-297, 2009.
48. X. O. Yang, R. Nurieva, G. J. Martinez, H. S. Kang, Y. Chung, B. P. Pappu, B. Shah, S. H. Chang, K. S. Schluns, S. S. Watowich, X. H. Feng, A. M. Jetten, and C. Dong, "Molecular antagonism and plasticity of regulatory and inflammatory T cell programs," Immunity, vol. 29, no. 1, pp. 44-56, Jul. 2008.
49. L. Zhou, J. E. Lopes, M. M. Chong, I. I. Ivanov, R. Min, G. D. Victora, Y. Shen, J. Du, Y. P. Rubtsov, A. Y. Rudensky, S. F. Ziegler, and D. R. Littman, "TGF-beta-induced Foxp3 inhibits T(H)17 cell differentiation by antagonizing RORgammat function," Nature, vol. 453, no. 7192, pp. 236-240, May 2008.