Agent-based models in translational systems biology

Wiley Interdisciplinary Reviews: Systems Biology and Medicine

Volumn 1, Issue 2, 2009, Pages 159-171

  An, Gary ^a,b   Mi, Qi ^b   Dutta Moscato, Joyeeta ^b,c   Vodovotz, Yoram ^b,c  

^a NORTHWESTERN UNIVERSITY   (United States)

^b UNIVERSITY OF PITTSBURGH   (United States)

^c UNIVERSITY OF PITTSBURGH MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HARNESS;

ANIMAL; BIOLOGICAL MODEL; BIOLOGY; HUMAN; REVIEW; STATISTICS; SYSTEMS BIOLOGY; TRANSLATIONAL RESEARCH;

ANIMALS; COMPUTATIONAL BIOLOGY; HUMANS; MODELS, BIOLOGICAL; STOCHASTIC PROCESSES; SYSTEMS BIOLOGY; TRANSLATIONAL RESEARCH;

EID: 79952117970     PISSN: 19395094     EISSN: 1939005X     Source Type: Journal    
DOI: 10.1002/wsbm.45     Document Type: Article

References (55)

1. An G. Concepts for developing a collaborative in silico model of the acute inflammatory response using agent-based modeling. J Crit Care 2006, 21:105-110; discussion 110-101.
2. Abbott R. The reductionist blind spot. Complexity 2009, 14:5, 10-22.
3. An G, Faeder J, Vodovotz Y. Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient. J Burn Care Res 2008, 29:277-285.
4. Vodovotz Y, Csete M, Bartels J, Chang S, An G. Translational systems biology of inflammation. PLoS Comput Biol 2008, 4:e1000014.
5. An G. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation. Theor Biol Med Model 2008, 5:11.
6. Fisher J, Henzinger TA. Executable cell biology. Nat Biotechnol 2007, 25:1239-1249.
7. Hunt CA, Ropella GE, Park S, Engelberg J. Dichotomies between computational and mathematical models. Nat Biotechnol 2008, 26:737-738; author reply 738-739.
8. Bankes SC. Agent-based modeling: a revolution?. Proc Natl Acad Sci U S A 2002, 99(suppl 3):7199-7200.
9. Bonabeau E. Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci U S A 2002, 99(suppl 3):7280-7287.
10. Grimm V, Revilla E, Berger U, Mooij W, Railsback S, et al. Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 2005, 310:987-991.
11. An G. Agent-based computer simulation and sirs: building a bridge between basic science and clinical trials. Shock 2001, 16:266-273.
12. Zhang L, Athale CA, Deisboeck TS. Development of a three-dimensional multiscale agent-based tumor model: simulating gene-protein interaction profiles, cell phenotypes andmulticellular patterns in brain cancer. J Theor Biol 2007, 244:96-107.
13. Engelberg JA, Ropella GE, Hunt CA. Essential operating principles for tumor spheroid growth. BMC Syst Biol 2008, 2:110.
14. Hunt CA, Ropella GE, Yan L, Hung DY, Roberts MS. Physiologically based synthetic models of hepatic disposition. J Pharmacokinet Pharmacodyn 2006, 33:737-772.
15. Reynolds CW. Flocks, herds, and schools: a distributed behavioral model in computer graphics. Comput Graphics 1987, 21:25-34 (SIGGRAPH '87 Conference Proceedings).
16. Lipniacki T, Paszek P, Brasier AR, Luxon BA, KimmelM. Stochastic regulation in early immune response. Biophys J 2006, 90:725-742.
17. Lipniacki T, Paszek P, Marciniak-Czochra A, Brasier AR, Kimmel M. Transcriptional stochasticity in gene expression. J Theor Biol 2006, 238:348-367.
18. Vodovotz Y, Clermont G, Hunt CA, Lefering R, Bartels J, et al. Evidence-based modeling of critical illness: an initial consensus from the Society for Complexity in Acute Illness. J Crit Care 2007, 22:77-84.
19. Wilensky U, Rand W. An introduction to agent-based modeling: modeling natural, social and engineered complex systems with NetLogo. Cambridge, MA: MIT Press; 2009.
20. Bailey AM, Lawrence MB, Shang H, Katz AJ, Peirce SM. Agent-based model of therapeutic adipose-derived stromal cell trafficking during ischemia predicts ability to roll on P-selectin. PLoS Comput Biol 2009, 5:e1000294.
21. Railsback SF, Lytinen SL, Jackson SK. Agent-based simulation platforms: review and development recommendations. Simulation 2006, 82:609-623.
22. Folcik VA, An GC, Orosz CG. The Basic Immune Simulator: an agent-based model to study the interactions between innate and adaptive immunity. Theor BiolMed Model 2007, 4:39.
23. Vodovotz Y, Constantine G, Rubin J, Csete M, Voit EO, et al. Mechanistic simulations of inflammation: Current state and future prospects. Math Biosci 2009, 217:1-10.
24. Ridgway D, Broderick G, Lopez-Campistrous A, Ru'aini M, Winter P, et al. Coarse-grained molecular simulation of diffusion and reaction kinetics in a crowded virtual cytoplasm. Biophys J 2008, 94:3748-3759.
25. Pogson M, Smallwood R, Qwarnstrom E, Holcombe M. Formal agent-based modelling of intracellular chemical interactions. Biosystems 2006, 85:37-45.
26. Pogson M, Holcombe M, Smallwood R, Qwarnstrom E. Introducing spatial information into predictive NFkappaB modelling-an agent-based approach. PLoS ONE 2008, 3:e2367.
27. An G. A model of TLR4 signaling and tolerance using a qualitative, particle-event-based method: introduction of spatially configured stochastic reaction chambers (SCSRC). Math Biosci 2009, 217:43-52.
28. Deisboeck TS, Berens ME, Kansal AR, Torquato S, Stemmer-Rachamimov AO, et al. Pattern of selforganization in tumour systems: complex growth dynamics in a novel brain tumour spheroid model. Cell Prolif 2001, 34:115-134.
29. Thorne BC, Bailey AM, Peirce SM. Combining experiments with multi-cell agent-based modeling to study biological tissue patterning. Brief Bioinform 2007, 8:245-257.
30. Grant MR, Mostov KE, Tlsty TD, Hunt CA. Simulating properties of in vitro epithelial cell morphogenesis. PLoS Comput Biol 2006, 2:e129.
31. Segovia-Juarez JL, Ganguli S, Kirschner D. Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model. J Theor Biol 2004, 231:357-376.
32. Chen S, Ganguli S, Hunt CA. An agent-based computational approach for representing aspects of in vitro multi-cellular tumor spheroid growth. Conf Proc IEEE Eng Med Biol Soc 2004, 1:691-694.
33. Yu W, Fang X, Ewald A, Wong K, Hunt CA, et al. Formation of cysts by alveolar type II cells in three-dimensional culture reveals a novel mechanism for epithelial morphogenesis. Mol Biol Cell 2007, 18:1693-1700.
34. Grant MR, Kim SH, Hunt CA. Simulating in vitro epithelial morphogenesis in multiple environments. Comput Syst Bioinformatics: Life Sci Soc 2006, 381-384.
35. Longo D, Peirce SM, Skalak TC, Davidson L, Marsden M, et al.Multicellular computer simulation of morphogenesis: blastocoel roof thinning and matrix assembly in Xenopus laevis. Dev Biol 2004, 271:210-222.
36. Peirce SM, Van Gieson EJ, Skalak TC. Multicellular simulation predicts microvascular patterning and in silico tissue assembly. Faseb J 2004, 18:731-733.
37. Walker DC, Hill G, Wood SM, Smallwood RH, Southgate J. Agent-based computational modeling of wounded epithelial cell monolayers. IEEE Trans Nanobioscience 2004, 3:153-163.
38. Mi Q, Riviere B, Clermont G, Steed DL, Vodovotz Y. Agent-based model of inflammation and wound healing: insights into diabetic foot ulcer pathology and the role of transforming growth factor-beta1. Wound Repair Regen 2007, 15:671-682.
39. Li NY, Verdolini K, Clermont G, Mi Q, Rubinstein EN, et al. A patient-specific in silico model of inflammation and healing tested in acute vocal fold injury. PLoS ONE 2008, 3:e2789.
40. Mansury Y, Diggory M, Deisboeck TS. Evolutionary game theory in an agent-based brain tumor model: exploring the 'Genotype-Phenotype' link. J Theor Biol 2006, 238:146-156.
41. Athale CA, Deisboeck TS. The effects of EGF-receptor density on multiscale tumor growth patterns. J Theor Biol 2006, 238:771-779.
42. Athale C, Mansury Y, Deisboeck TS. Simulating the impact of a molecular 'decision-process' on cellular phenotype and multicellular patterns in brain tumors. J Theor Biol 2005, 233:469-481.
43. Wakeland W, Macovsky L, An G. A hybrid simulation for studying the acute inflammatory response. Proceedings of the 2007 Spring Simulation Multiconference (Agent Directed Simulation Symposium) 2007, 1:39-46.
44. Kitano H, Oda K. Robustness trade-offs and hostmicrobial symbiosis in the immune system. Mol Syst Biol 2006, 2. doi:10.1038/msb410003.
45. Kitano H. Towards a theory of biological robustness. Mol Syst Biol 2007, 3:137. doi:10.1038/msb4100179.
46. Broderick G, Ru'ainiM, Chan E, EllisonMJ. A life-like virtual cell membrane using discrete automata. In Silico Biol 2005, 5:163-178.
47. Abbott RG, Forrest S, Pienta KJ. Simulating the hallmarks of cancer. Artif Life 2006, 12:617-634.
48. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000, 100:57-70.
49. Merlo LM, Pepper JW, Reid BJ, Maley CC. Cancer as an evolutionary and ecological process. Nat Rev 2006, 6:924-935.
50. Pepper JW, Sprouffske K, Maley CC. Animal cell differentiation patterns suppress somatic evolution. PLoS Comput Biol 2007, 3(12):e250. doi:10.1371/journal.pcbi.0030250.
51. Tang J, Ley KF, Hunt CA. Dynamics of in silico leukocyte rolling, activation, and adhesion. BMC Syst Biol 2007, 1:14.
52. An G. In silico experiments of existing and hypothetical cytokine-directed clinical trials using agent-based modeling. Critical care medicine 2004, 32:2050-2060.
53. Bailey AM, Thorne BC, Peirce SM. Multi-cell agentbased simulation of the microvasculature to study the dynamics of circulating inflammatory cell trafficking. Ann Biomed Eng 2007, 35:916-936.
54. Richards RS, D'Souza R, Lysenko M, An G. Dataparallel techniques for agent-based tissue modeling on graphical processing units. Design Engineering Technical Conference and Computers and Information in Engineering Conference. New York, 2008.
55. Kevrekidis I, Gear C, Hummer G. Equation-free: the computer-aided analysis of complexmultiscale systems. AIChE J 2004, 50:1346-1355.