Agent-based modeling and biomedical ontologies: A roadmap

Wiley Interdisciplinary Reviews: Computational Statistics

Volumn 3, Issue 4, 2011, Pages 343-356

  An, Gary ^a   Christley, Scott ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGENT-BASED MODEL; AGENT-BASED MODELING; BIOMEDICAL ONTOLOGIES; BIOMEDICAL RESEARCH; COMPUTATIONAL AGENTS; META STRUCTURES; MODELING AND SIMULATION; ROADMAP; TECHNOLOGICAL ENHANCEMENT; THROUGHPUT CAPACITIES;

BIOLOGICAL SYSTEMS; COMPUTATIONAL METHODS; COMPUTER SIMULATION; INTELLIGENT AGENTS; KNOWLEDGE REPRESENTATION;

ONTOLOGY;

EID: 79958134210     PISSN: 19395108     EISSN: 19390068     Source Type: Journal    
DOI: 10.1002/wics.167     Document Type: Article

References (54)

1. United States Food and Drug Administration Report: Innovation or Stagnation. Challenge and opportunity on the critical path to new medical products Available at: (Accessed February 1, 2011).
2. An G. Closing the scientific loop: bridging correlation and causality in the petaflop age. Sci Transl Med 2010, 2:41ps34.
3. Uschold M, Gruninger M. Ontologies: principles, methods and applications. Knowl Eng Rev 2009, 11:93-136.
4. Consortium TGO. Gene ontology: tool for the unification of biology. Nat Genet 2000, 25:25-29.
5. Noy NF, Shah NH, Whetzel PL, Dai B, Dorf M, Griffith N, Jonquet C, Rubin DL, Storey MA, Chute CG, Musen, MA. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res 2009, 1:170-173.
6. Rubin DL, Lewis SE, Mungall CJ, Misra S, Westerfield M, Ashburner M, Sim I, Chute CG, Solbrig H, Storey MA, Smith B, Day-Richter J, Noy NF, Musen MA. National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge. OMICS 2006, 10:185-198.
7. Jeong E, Nagasaki M, Miyano S. Rule-based reasoning for system dynamics in cell systems. Genome Inform 2008, 20:25-36.
8. Takai-Igarashi T. Ontology based standardization of Petri net modeling for signaling pathways. In Silico Biol 2005, 5:529-536.
9. Shegogue D, Zheng WJ. Integration of the gene ontology into an object-oriented architecture. BMC Bioinformatics 2005, 6:113.
10. Ruebenacker O, Moraru II, Schaff JC, Blinov ML. Kinetic modeling using BioPAX ontology. Proceedings (IEEE Int Conf Bioinformatics Biomed) 2007, 2007:339-348.
11. Jeong E, Nagasaki M, Salto A, Miyano S. Cell system ontology: representation for modeling, visualizing and simulating biological pathways. In Silico Biol 2007, 7:623-638.
12. Lister AL, Lord P, Pocock M, Wipat A. Annotation of SBML models through rule-based semantic integration. J Biomed Semantics 2010, 1(Suppl 1):S3.
13. An G, Mi Q, Dutta-Moscato J, Vodovotz Y. Agent-based models in translational systems biology. Wiley Interdiscip Rev Syst Biol Med 2009, 1:159-171.
14. Bonabeau E. Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci USA 2002, 99(Suppl 3):7280-7287.
15. Bankes SC. Agent-based modeling: a revolution? Proc Natl Acad Sci USA 2002, 99(Suppl 3):7199-7200.
16. Hunt CA, Ropella GE, Lam TN, Tang J, Kim SH, Engelberg JA, Sheikh-Bahaei S. At the biological modeling and simulation frontier. Pharm Res 2009, 26:2369-2400.
17. Walker DC, Southgate J. The virtual cell-a candidate co-ordinator for 'middle-out' modeling of biological systems. Briefings Bioinform 2009, 10:450-461.
18. 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.
19. Kirschner DE, Chang ST, Riggs TW, Perry N, Linderman JJ. Toward a multiscale model of antigen presentation in immunity. Immunol Rev 2007, 216:93-118.
20. Zhang L, Athale CA, Deisboeck TS. Development of a three-dimensional multiscale agent-based tumor model: simulating gene-protein interaction profiles, cell phenotypes and multicellular patterns in brain cancer. J Theor Biol 2007, 244:96-107.
21. Christley S, Alber MS, Newman SA. Patterns of mesenchymal condensation in a multiscale, discrete stochastic model. PLos Comput Biol 2007, 3:e76.
22. Santoni D, Pedicini M, Castiglione F. Implementation of a regulatory gene network to simulate the TH1/2 differentiation in an agent-based model of hypersensitivity reactions. Bioinformatics 2008, 24:1374-1380.
23. An G. Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models. Methods Mol Biol (Clifton, NJ) 2009, 500:445-468.
24. 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.
25. An G. Agent-based computer simulation and sirs: building a bridge between basic science and clinical trials. Shock 2001, 16:266-273.
26. An G. In silico experiments of existing and hypothetical cytokine-directed clinical trials using agent-based modeling. Crit Care Med 2004, 32:2050-2060.
27. 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.
28. Engelberg JA, Ropella GE, Hunt CA. Essential operating principles for tumor spheroid growth. BMC Syst Biol 2008, 2:110.
29. Deisboeck TS, Berens ME, Kansal AR, Torquato S, Stemmer-Rachamimov AO, Chiocca EA. Pattern of self-organization in tumour systems: complex growth dynamics in a novel brain tumour spheroid model. Cell Proliferat 2001, 34:115-134.
30. 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.
31. Thorne BC, Bailey AM, Benedict K, Peirce-Cottler S. Modeling blood vessel growth and leukocyte extravasation in ischemic injury: an integrated agent-based and finite element analysis approach. J Crit Care 2006, 21:346.
32. Tang J, Ley KF, Hunt CA. Dynamics of in silico leukocyte rolling, activation, and adhesion. BMC Syst Biol 2007, 1:14.
33. Tang J, Hunt CA, Mellein J, Ley K. Simulating leukocyte-venule interactions-a novel agent-oriented approach. Conf Proc IEEE Eng Med Biol Soc 2004, 7:4978-4981.
34. Bailey AM, Thorne BC, Peirce SM. Multi-cell agent-based simulation of the microvasculature to study the dynamics of circulating inflammatory cell trafficking. Ann Biomed Eng 2007, 35:916-936.
35. 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.
36. 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.
37. Adra S, Sun T, MacNeil S, Holcombe M, Smallwood R. Development of a three dimesional multiscale computational model of the human epidermis. PLoS ONE 2010, 5:e8511.
38. 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.
39. Broderick G, Ru'aini M, Chan E, Ellison MJ. A life-like virtual cell membrane using discrete automata. In Silico Biol 2005, 5:163-178.
40. Pogson M, Holcombe M, Smallwood R, Qwarnstrom E. Introducing spatial information into predictive NF-kappaB modelling-an agent-based approach. PLoS ONE 2008, 3:e2367.
41. Pogson M, Smallwood R, Qwarnstrom E, Holcombe M. Formal agent-based modelling of intracellular chemical interactions. Bio Systems 2006, 85:37-45.
42. Ridgway D, Broderick G, Lopez-Campistrous A, Ru'aini M, Winter P, Hamilton M, Boulanger P, Kovalenko A, Ellison MJ. Coarse-grained molecular simulation of diffusion and reaction kinetics in a crowded virtual cytoplasm. Biophys J 2008, 94: 3748-3759.
43. Troisi A, Wong V, Ratner MA. An agent-based approach for modeling molecular self-organization. Proc Natl Acad Sci USA 2005, 102:255-260.
44. Hoehme S, Drasdo D. A cell-based simulation software for multi-cellular systems. Bioinformatics 2010, 26:2641-2642.
45. Colasanti R, An G. The abstracted biological computational unit (ABCU): introduction of a recursive descriptor for multi-scale computational modeling of biological systems. J Crit Care 2009, 24:e35-36.
46. Benjamin P, Patki M, Mayer R. Using ontologies for simulation modeling. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA; 2006, 1151-1159.
47. Petty MD, Weisel EW. A composability lexicon. Proceedings of the 2003 Spring Simulation Conference, Orlando, FL; 2003, 181-187.
48. Yilmaz L. A Strategy for improving dynamic composability: ontology-driven introspective agent architectures. J Syst Cybern Inf 2007, 5:1-9.
49. Alonso-Calvo R, Maojo V, Billhardt H, Martin-Sanchez F, Garcia-Remesai M, Perez-Rey D. An agent- and ontology-based system for integrating public gene, protein and disease databases. J Biomed Inform 2007, 40:17-29.
50. Bartocci E, Cacciagrano D, Cannata N, Corradini F, Merelli E, Milanesi L, Romano P. An agent-based multilayer architecture for bioinformatics grids. IEEE Trans Nanobioscience 2007, 6:142-148.
51. Merelli E, Armano G, Cannata N, Corradini F, d'Inverno M, Doms A, Lord P, Martin A, Milanesi L, Moller S, et al.Agents in bioinformatics, computational and systems biology. Brief Bioinform 2006, 8:45-59.
52. Keele JW, Wray JE. Software agents in molecular computational biology. Brief Bioinform 2005, 6:370-379.
53. Karasavvas KA, Baldock R, Burger A. Bioinformatics integration and agent technology. J Biomed Inform 2004, 37:205-219.
54. Fishwick PA, Miller JA. Ontologies for modeling and simulation: issues and approaches. Proceedings of the 2004 Winter Simulation Conference, Washington, DC; 2004, 259-264.