Multiscale computational models of complex biological systems

Annual Review of Biomedical Engineering

Volumn 15, Issue , 2013, Pages 137-154

  Walpole, Joseph ^a   Papin, Jason A ^a   Peirce, Shayn M ^a  

^a University of Virginia   (United States)

Author keywords

biochemical networks; bioinformatics; data integration; model design; model validation; systems biology

Indexed keywords

BIOCHEMICAL NETWORK; BIOLOGICAL PHENOMENA; COMPLEX BIOLOGICAL SYSTEMS; EXPERIMENTAL METHODOLOGY; MODEL DESIGN; MODEL VALIDATION; MULTISCALE COMPUTATIONAL MODEL; SYSTEMS BIOLOGY;

BIOINFORMATICS; BIOMEDICAL ENGINEERING; COMPLEX NETWORKS; DATA INTEGRATION;

BIOLOGICAL SYSTEMS;

PLATELET DERIVED GROWTH FACTOR; PLATELET DERIVED GROWTH FACTOR RECEPTOR;

BIOINFORMATICS; BIOLOGICAL MODEL; BIOMEDICAL ENGINEERING; COMPUTER MODEL; DIABETIC RETINOPATHY; DIABETOGENESIS; DISEASE MODEL; HUMAN; INTERMETHOD COMPARISON; NOMENCLATURE; PATHOPHYSIOLOGY; QUANTITATIVE ANALYSIS; REVIEW; SYSTEMS BIOLOGY; TAXONOMY; VALIDATION PROCESS; VIRTUAL REALITY;

ANIMALS; BIOMEDICAL ENGINEERING; COMPUTATIONAL BIOLOGY; HUMANS; MODELS, BIOLOGICAL; RESEARCH DESIGN; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; THERMODYNAMICS; TISSUE ENGINEERING;

EID: 84880559564     PISSN: 15239829     EISSN: 15454274     Source Type: Book Series    
DOI: 10.1146/annurev-bioeng-071811-150104     Document Type: Review

References (68)

1. Frank RN. 2004. Diabetic retinopathy. N. Engl. J. Med. 350:48-58
2. Geraldes P, Hiraoka-Yamamoto J, Matsumoto M, Clermont A, Leitges M, et al. 2009. Activation of PKC-δ and SHP-1 by hyperglycemia causes vascular cell apoptosis and diabetic retinopathy. Nat. Med. 15:1298-306
3. Modi SR, Camacho DM, Kohanski MA, Walker GC, Collins JJ. 2011. Functional characterization of bacterial sRNAs using a network biology approach. Proc. Natl. Acad. Sci. USA 108:15522-27
4. Seok J, Xiao W, Moldawer LL, Davis RW, Covert MW. 2009. A dynamic network of transcription in LPS-Treated human subjects. BMC Syst. Biol. 3:78
5. Barua D, Kim J, Reed JL. 2010. An automated phenotype-Driven approach (GeneForce) for refining metabolic and regulatory models. PLoS Comput. Biol. 6:e1000970
6. Milne CB, Eddy JA, Raju R, Ardekani S, Kim PJ, et al. 2011. Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052. BMC Syst. Biol. 5:130
7. Cosgrove BD, Alexopoulos LG, Saez-Rodriguez J,Griffith LG, Lauffenburger DA. 2009. Amultipathway phosphoproteomic signaling network model of idiosyncratic drug-And inflammatory cytokine-induced toxicity in human hepatocytes. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2009:5452-55
8. Eissing T, Kuepfer L, Becker C, Block M, Coboeken K, et al. 2011. A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks. Front. Physiol. 2:4
9. Shirinifard A, Gens JS, Zaitlen BL, Poplawski NJ, Swat M, Glazier JA. 2009. 3D multi-cell simulation of tumor growth and angiogenesis. PLoS ONE 4:e7190
10. Folcik VA, Broderick G, Mohan S, Block B, Ekbote C, et al. 2011. Using an agent-basedmodel to analyze the dynamic communication network of the immune response. Theor. Biol. Med. Model. 8:1
11. Caputo KE, Hammer DA. 2009. Adhesive dynamics simulation of G-protein-mediated chemokineactivated neutrophil adhesion. Biophys. J. 96:2989-3004
12. Pospieszalska MK, Zarbock A, Pickard JE, Ley K. 2009. Event-Tracking model of adhesion identifies load-bearing bonds in rolling leukocytes. Microcirculation 16:115-30
13. Fallahi-Sichani M, Kirschner DE, Linderman JJ. 2012. NF-κB signaling dynamics play a key role in infection control in tuberculosis. Front. Physiol. 3:170
14. Brown BN, Price IM, Toapanta FR, DeAlmeida DR, Wiley CA, et al. 2011. An agent-based model of inflammation and fibrosis following particulate exposure in the lung. Math. Biosci. 231:186-96
15. Scheff JD, Mavroudis PD, Calvano SE, Lowry SF, Androulakis IP. 2011. Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia. Physiol. Genomics 43:951-64
16. Sander EA, Stylianopoulos T, Tranquillo RT, Barocas VH. 2009. Image-based multiscale modeling predicts tissue-level and network-level fiber reorganization in stretched cell-compacted collagen gels. Proc. Natl. Acad. Sci. USA 106:17675-80
17. Sharafi B, Ames EG, Holmes JW, Blemker SS. 2011. Strains at the myotendinous junction predicted by a micromechanical model. J. Biomech. 44:2795-801
18. Adra S, Sun T, MacNeil S, Holcombe M, Smallwood R. 2010. Development of a three dimensional multiscale computational model of the human epidermis. PLoS ONE 5:e8511
19. Greenstein JL, Winslow RL. 2011. Integrative systems models of cardiac excitation-contraction coupling. Circ. Res. 108:70-84
20. Moreno JD, Zhu ZI, Yang PC, Bankston JR, Jeng MT, et al. 2011. A computational model to predict the effects of class I anti-Arrhythmic drugs on ventricular rhythms. Sci. Transl. Med. 3:98ra83
21. Thorne BC, Hayenga HN, Humphrey JD, Peirce SM. 2011. Toward a multi-scale computational model of arterial adaptation in hypertension: Verification of a multi-cell agent based model. Front. Physiol. 2:20
22. Holland DO, Krainak NC, Saucerman JJ. 2011. Graphical approach to model reduction for nonlinear biochemical networks. PLoS ONE 6:e23795
23. Schmidt BJ, Papin JA, Lawrence MB. 2009. Nano-motion dynamics are determined by surface-Tethered selectin mechanokinetics and bond formation. PLoS Comput. Biol. 5:e1000612
24. Bailey AM, Thorne BC, Peirce SM. 2007. Multi-cell agent-based simulation of the microvasculature to study the dynamics of circulating inflammatory cell trafficking. Ann. Biomed. Eng. 35:916-36
25. Friedl P, Wolf K. 2010. Plasticity of cell migration: A multiscale tuning model. J. Cell Biol. 188:11-19
26. Grima R. 2008. Multiscale modeling of biological pattern formation. Curr. Top. Dev. Biol. 81:435-60
27. N'Dri NA, Shyy W, Tran-Son-Tay R. 2003. Computational modeling of cell adhesion and movement using a continuum-kinetics approach. Biophys. J. 85:2273-86
28. Brodland GW, Chen X, Lee P, Marsden M. 2010. From genes to neural tube defects (NTDs): Insights from multiscale computational modeling. HFSP J. 4:142-52
29. Sample C, Shvartsman SY. 2010. Multiscale modeling of diffusion in the early Drosophila embryo. Proc. Natl. Acad. Sci. USA 107:10092-96
30. Tomlin CJ, Axelrod JD. 2007. Biology by numbers: Mathematical modelling in developmental biology. Nat. Rev. Genet. 8:331-40
31. von Dassow G, Meir E, Munro EM, Odell GM. 2000. The segment polarity network is a robust developmental module. Nature 406:188-92
32. Meir E, Munro EM, OdellGM, VonDassowG. 2002. Ingeneue: A versatile tool for reconstituting genetic networks, with examples from the segment polarity network. J. Exp. Zool. 294:216-51
33. Longo D, Peirce SM, Skalak TC,Davidson L,Marsden M, et al. 2004. Multicellular computer simulation of morphogenesis: Blastocoel roof thinning and matrix assembly in Xenopus laevis. Dev. Biol. 271:210-22
34. Silva JR, Rudy Y. 2010. Multi-scale electrophysiology modeling: From atom to organ. J. Gen. Physiol. 135:575-81
35. Aguado-Sierra J, Krishnamurthy A, Villongco C, Chuang J, Howard E, et al. 2011. Patient-specific modeling of dyssynchronous heart failure: A case study. Prog. Biophys. Mol. Biol. 107:147-55
36. Newman SA, Christley S, Glimm T, Hentschel HG, Kazmierczak B, et al. 2008. Multiscale models for vertebrate limb development. Curr. Top. Dev. Biol. 81:311-40
37. Das A, Lauffenburger D, Asada H, Kamm RD. 2010. A hybrid continuum-Discrete modelling approach to predict and control angiogenesis: Analysis of combinatorial growth factor and matrix effects on vesselsprouting morphology. Philos. Trans. R. Soc. A 368:2937-60
38. Liu G, Qutub AA, Vempati P, Mac Gabhann F, Popel AS. 2011. Module-based multiscale simulation of angiogenesis in skeletal muscle. Theor. Biol. Med. Model. 8:6
39. Vempati P, Popel AS, Mac Gabhann F. 2011. Formation of VEGF isoform-specific spatial distributions governing angiogenesis: Computational analysis. BMC Syst. Biol. 5:59
40. Bauer AL, JacksonTL, Jiang Y, Rohlf T. 2010. Receptor cross-Talk in angiogenesis: Mapping environmental cues to cell phenotype using a stochastic, Boolean signaling network model. J. Theor. Biol. 264:838-46
41. Hashambhoy YL, Chappell JC, Peirce SM, Bautch VL,Mac Gabhann F. 2011. Computational modeling of interacting VEGF and soluble VEGF receptor concentration gradients. Front. Physiol. 2:62
42. Causey L, Cowin SC, Weinbaum S. 2012. Quantitative model for predicting lymph formation and muscle compressibility in skeletal muscle during contraction and stretch. Proc. Natl. Acad. Sci. USA 109:9185-90
43. Coddington EA, Levinson N. 1955. Theory of Ordinary Differential Equations. New York: McGraw-Hill. 429 p.p.
44. Fallahi-SichaniM, Flynn JL, Linderman JJ, KirschnerDE. 2012. Differential risk of tuberculosis reactivation among anti-TNF therapies is due to drug binding kinetics and permeability. J. Immunol. 188:3169-78
45. Quo CF, Moffitt RA, Merrill AH,Wang MD. 2011. Adaptive control model reveals systematic feedback and key molecules in metabolic pathway regulation. J. Comput. Biol. 18:169-82
46. Laise P, Di Patti F, Fanelli D, Masselli M, Arcangeli A. 2011. Deterministic and stochastic aspects of VEGF-A production and the cooperative behavior of tumoral cell colony. J. Theor. Biol. 272:55-63
47. Sun T, Adra S, Smallwood R, Holcombe M, MacNeil S. 2009. Exploring hypotheses of the actions of TGF-β1 in epidermal wound healing using a 3Dcomputationalmultiscale model of the human epidermis. PLoS ONE 4:e8515
48. Haggart CR, Bartell JA, Saucerman JJ, Papin JA. 2011. Whole-genome metabolic network reconstruction and constraint-based modeling. Methods Enzymol. 500:411-33
49. Tveito A, LinesGT, Edwards AG, MaleckarMM,Michailova A, et al. 2012. Slow calcium-Depolarizationcalcium waves may initiate fast local depolarization waves in ventricular tissue. Prog. Biophys. Mol. Biol. 110:295-304
50. Thompson AB, Gayzik FS,Moreno DP, Rhyne AC, Vavalle NA, Stitzel JD. 2012. A paradigm for human body finite element model integration from a set of regional models. Biomed. Sci. Instrum. 48:423-30
51. ZhangX,Gan RZ. 2011. A comprehensive model of human ear for analysis of implantable hearing devices. IEEE Trans. Biomed. Eng. 58:3024-27
52. ZahedmaneshH, Lally C. 2011. A multiscale mechanobiological modelling framework using agent-based models and finite element analysis: Application to vascular tissue engineering. Biomech. Model. Mechanobiol. 11:363-77
53. Goktepe S, Abilez OJ, Parker KK, Kuhl E. 2010. A multiscale model for eccentric and concentric cardiac growth through sarcomerogenesis. J. Theor. Biol. 265:433-42
54. Du P, O'Grady G, Davidson JB, Cheng LK, Pullan AJ. 2010. Multiscale modeling of gastrointestinal electrophysiology and experimental validation. Crit. Rev. Biomed. Eng. 38:225-54
55. Trayanova NA, Rice JJ. 2011. Cardiac electromechanical models: From cell to organ. Front. Physiol. 2:43
56. Artel A, Mehdizadeh H, Chiu YC, Brey EM, Cinar A. 2011. An agent-based model for the investigation of neovascularization within porous scaffolds. Tissue Eng. Part A 17:2133-41
57. Bentley K, Gerhardt H, Bates PA. 2008. Agent-based simulation of notch-mediated tip cell selection in angiogenic sprout initialisation. J. Theor. Biol. 250:25-36
58. Qu Z, Garfinkel A, Weiss JN, Nivala M. 2011. Multi-scale modeling in biology: How to bridge the gaps between scales? Prog. Biophys. Mol. Biol. 107:21-31
59. Valentin A, Humphrey JD. 2009. Evaluation of fundamental hypotheses underlying constrained mixture models of arterial growth and remodelling. Philos. Trans. R. Soc. A 367:3585-606
60. Valentin A, Humphrey JD. 2009. Parameter sensitivity study of a constrained mixture model of arterial growth and remodeling. J. Biomech. Eng. 131:101006
61. HayengaHN,Thorne BC, Peirce SM, Humphrey JD. 2011. Ensuring congruency in multiscale modeling: Towards linking agent based and continuum biomechanical models of arterial adaptation. Ann. Biomed. Eng. 39:2669-82
62. Fedosov DA, Lei H, Caswell B, Suresh S, Karniadakis GE. 2011. Multiscale modeling of red blood cell mechanics and blood flow in malaria. PLoS Comput. Biol. 7:e1002270
63. Kim MJ, Maly IV. 2009. Deterministic mechanical model of T-killer cell polarization reproduces the wandering of aim between simultaneously engaged targets. PLoS Comput. Biol. 5:e1000260
64. Singh S, Narang AS, Mahato RI. 2011. Subcellular fate and off-Target effects of siRNA, shRNA, and miRNA. Pharm. Res. 28:2996-3015
65. Bassingthwaighte JB. 2010. Predictive modeling and integrative physiology: The Physiome Projects. Open Pacing Electrophysiol. Ther. J. 3:66-74
66. Bassingthwaighte JB, Chizeck HJ. 2008. The Physiome Projects and multiscale modeling. IEEE Signal Process. Mag. 25:121-44
67. Nawroth JC, Lee H, Feinberg AW, RipplingerCM, McCain ML, et al. 2012. A tissue-engineered jellyfish with biomimetic propulsion. Nat. Biotechnol. 30:792-97
68. Callura JM, Cantor CR, Collins JJ. 2012. Genetic switchboard for synthetic biology applications. Proc. Natl. Acad. Sci. USA 109:5850-55