Computational Biology Modeling across Different Scales
Filippo Castiglione, Francesco Pappalardo
2013
Abstract
One of the most formidable challenges in modern biology is to get a unified view of the various mechanisms governing the behavior and of the causal relationships among different parts of a living system. It is coming clearer nowadays that to get such comprehensive picture computational models embracing different observation levels in space and time have to be formulated to explain the enormous amount of data deriving from -omic high throughput measurements methods. In this article we aim at giving a meaning to the concept of multi-scale modeling in the framework of studies of biological systems with particular interest in understanding human physiology in disease conditions.
References
- Alberghina L, Westerhoof HV. Systems Biology. Definitions and perspectives. Heidelberg; Springer, 2008.
- Bailey NTJ. The Elements of Stochastic Processes with Applications to the Natural Sciences. New York; Wiley, 1990.
- Bassingthwaighte JB, Chizeck HJ, Atlas LE, et al. Multiscale modeling of cardiac cellular energetics. Ann. N. Y. Acad. Sci. 2005; 1047:395-424.
- Baum LE, Petrie T. Statistical Inference for Probabilistic Functions of Finite State Markov Chains. The Annals of Mathematical Statistics 1966; 37(6):1554-1563.
- Bradley C, Bowery A, Britten R, et al. OpenCMISS: a multi-physics & multi-scale computational infrastructure for the VPH/Physiome project. Prog. Biophys. Mol. Biol. 2011; 101:32-47.
- Brenner S. Biological computation. In: Bock G, Goode J (Eds.). The limits of reductionism in biology. Novartis Foundation Symposium, vol. 213. London UK: Wiley, 1998, 106-116.
- Brown K. S., Hill C. C., Calero G. A., et al. The statistical mechanics of complex signaling networks: nerve growth factor signaling. Phys. Biol. 2004; 1(3-4):184- 195.
- Caiazzo A, Evans D, Falcone J-L, et al. A Complex Automata approach for in-stent restenosis: Twodimensional multiscale modelling and simulations. J. Comp. Science, 2011; 2(1):9-17.
- Castiglione F, Liso A, Bernaschi M, Succi S. Microscopic simulation in biology and medicine. Current Medicinal Chemistry 2007; 14(6):625-637.
- Christie GR, Nielsen PMF, Blackett SA, et al. FieldML: concepts and implementation. Phil. Trans. R. Soc. A 2009; 367(1895):1869-1884.
- Coveney PV, Fowler PW. Modelling biological complexity: a physical scientist's perspective. J. R Soc. Interface 2005; 2:267-280.
- Dada JO, Mendes P. Multi-scale modelling and simulation in systems biology. Integr. Biol. 2011; 3:86-96.
- Deane C. M., Salwinski L, Xenarios I, et al. Protein interactions: two methods for assessment of the reliability of high throughput observations. Mol. Cell. Proteomics 2002; 1:349-356.
- de Graaf A. A., Freidig AP, De Roos B, et al. Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology. PLoS Comp. Biol.; 2009 5(11):e1000554.
- Di Ventura B, Lemerle C, Michalodimitrakis K, et al. From in vivo to in silico biology and back. Nature 2006; 443(7111):527-533.
- Drasdo D, Kree R, McCaskill JS. A Monte Carlo Model to tissue cell populations. Phys. Rev. E 1995; 52(6):6635-6657.
- Drasdo D. Buckling Instabilities in One-Layered Growing Tissues. Phys. Rev. Lett.; 2000 84:4424-4427.
- Evans D, Lawford P, Gunn J, et al. The application of multiscale modelling to the process of development and prevention of stenosis in a stented coronary artery. Phil.Trans. R. Soc. A, 2008; 366:3343-3360.
- Eissing T, Kuepfer L, Becker C, et al. A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks. Frontiers in Physiology; 2011 2(4):1-10.
- Engler AJ, Humbert PO, Wehrle-Haller B, et al. Multiscale modeling of form and function. Science 2009; 324:208-212.
- Falcone J, Chopard B, Hoekstra A. MML: towards a Multiscale Modeling Language. Procedia Computer Science, 2010; 1(1):819-826.
- Fish J (Ed.) Multiscale Methods, bridging the scales in science and engineering. Oxford: Oxford University Press, 2010.
- Garny A, Nickerson DP, Cooper J, et al. CellML and associated tools and techniques. Philos Transact A Math Phys Eng Sci. 2008; 366(1878):3017-3043.
- Gillespie DT. A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions. J. Comp. Phys. 1976; 22 (4):403- 434.
- Gillespie DT. Exact Stochastic Simulation of Coupled Chemical Reactions. J. Phys. Chem. 1977; 81(25):2340-2361.
- Grima R. Multiscale modeling of biological pattern formation. Curr. Top. Dev. Biol. 2008; 81:435-460.
- Gutenkunst RN, Waterfall JJ, Casey FP, et al. Universally sloppy parameter sensitivities in systems biology models. PLoS Comput. Biol. 2007; 3:1871-1878.
- Hoehme S, Brulport M, Bauer A, et al. Cell alignment along micro-vessels as order principle to restore tissue architecture during liver regeneration: from experiment to virtual tissues and back. Proc. Natl. Acad. Sci. USA; 2010 107(23):10371-10376.
- Holzhütter H-G, Drasdo D, Preusser T, et al. The virtual liver: a multidisciplinary, multilevel challenge for systems biology. Wiley Interdiscip. Rev. Syst. Biol. Med. 2012; 4(3):221-235.
- Hucka M, Finney A, Sauro HM, et al. The Systems Biology Markup Language (SBML): A Medium for Representation and Exchange of Biochemical Network Models. Bioinformatics 2003; 9(4):524-531.
- Hunter PJ, Borg TK. Integration from proteins to organs: the Physiome Project. Nat. Rev. 2003; 4:237-243.
- Hunter P., Nielsen P. A., Strategy for integrative Computational physiology. Physiology 2005; 20:316-325.
- Hunter PJ, Viceconti M. The VPH-Physiome Project: Standards and Tools for Multiscale Modeling in Clinical Applications. IEEE Reviews in Biomedical Engineering 2009; 2:40-53.
- Joshi H, Singharoy AB, Sereda YV, et al. Multiscale simulation of microbe structure and dynamics. Prog. Biophys. Mol. Biol. 2011; 107:200-217.
- Kevrekidis IG, Gear CW, Hyman JM, et al. Equation-free, coarse-grained multiscale computation: enabling microscopic simulators to perform system-level tasks. Comm. Math. Sciences 2003; 1(4):715-762.
- Kitano H. Systems Biology: A Brief Overview. Science 2002; 295(5560):1662-1664.
- Kohl P, Crampin EJ, Quinn TA, et al. Systems biology: an approach. Clin. Pharmacol. Ther.; 2010 88:25-33.
- Meier-Schellersheim M., Fraser I. D., Klauschen F., Multiscale modeling for biologists. Wiley Interdiscip. Rev. Syst. Biol. Med. 2009; 1:4-14.
- Mendoza L. A network model for the control of the differentiation process in Th cells. Bio. Systems 2006; 84:101-114.
- Mendoza L, Pardo F. A robust model to describe the differentiation of T-helper cells. Theory Biosci. 2010; 129(4):283-293.
- Murray JD. Mathematical Biology vol I and vol II. NY: Springer-Verlag, 2003.
- Murtola T, Bunker A, Vattulainen I, et al. Multiscale modeling of emergent materials: biological and soft matter. Phys. Chem. Chem. Phys. 2009; 11:1869- 1892.
- Noble D. Modeling the heart - from genes to cells to the whole organ. Science 2002; 295:1678-1682.
- Noble D. The Music of Life. Biology Beyond the Genome. Oxford UK: Oxford University Press, 2006.
- Normile D. Building Working Cells 'in Silico'. Science 1999; 284(5411):80-81.
- Plewa T, Linde T, Weirs VG. Adaptive Mesh Refinement - Theory and Applications. Lect. Notes Comp. Sci. and Eng. 2005; 41:341-350.
- Qu Z, Garfinkel A, Weiss JN, Nivala M. Multi-scale modeling in biology: How to bridge the gaps between scales? Prog. Biophys. Mol. Biol. 2011; 107:21-31.
- Ribba B, Sautb O, Colin T, et al. A multiscale mathematical model of avascular tumor growth to investigate the therapeutic benefit of anti-invasive agents. J. Theo. Biol. 2006; 243(4):532-541.
- 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.
- Schaff J, Fink CC, Slepchenko B, et al. A general computational framework for modeling cellular structure and function. Biophys. J. 1997; 73:1135- 1146.
- Schnell S, Grima R, Maini PK. Multiscale modeling in biology. Am. Scientist 2007; 95:134-142.
- Smallbone K, Simeonidis E, Broomhead DS, et al. Something from nothing: bridging the gap between constraint-based and kinetic modelling. FEBS J 2007; 274:5576-5585.
- Sloot PMA, Hoekstra AG. Multi-scale modelling in computational biomedicine. Brief. Bioinform. 2010; 11(1):142-152.
- Southern J, Pitt-Francis J, Whiteley J, et al. Multi-scale computational modelling in biology and physiology. Prog. Biophys. Mol. Bio. 2008; 96(1-3):60-89.
- Tahir H, Hoekstra AG, Lorenz E, et al. Multi-scale simulations of the dynamics of in-stent restenosis: impact of stent deployment and design. Interface Focus 2011; 1(3):365-373.
- Takahashi K, Kaizu K, Hu B, et al. A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics 2004; 20:538-546.
- Tyson JT. What Everyone Should Know about the Belousov-Zhabotinsky Reaction. In: Levin SA (Ed.). Frontiers in Mathematical Biology. NY: Springer Verlag, 1994, 569-587.
- Viceconti M. Multiscale Modeling of the Skeletal System. NY: Cambridge Univ. Press, 2012.
- Weinan E. Principles of multiscale modeling. NY: Cambridge Univ. Press, 2011.
Paper Citation
in Harvard Style
Castiglione F. and Pappalardo F. (2013). Computational Biology Modeling across Different Scales . In Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: BIOMED, (SIMULTECH 2013) ISBN 978-989-8565-69-3, pages 617-625. DOI: 10.5220/0004405706170625
in Bibtex Style
@conference{biomed13,
author={Filippo Castiglione and Francesco Pappalardo},
title={Computational Biology Modeling across Different Scales},
booktitle={Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: BIOMED, (SIMULTECH 2013)},
year={2013},
pages={617-625},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004405706170625},
isbn={978-989-8565-69-3},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: BIOMED, (SIMULTECH 2013)
TI - Computational Biology Modeling across Different Scales
SN - 978-989-8565-69-3
AU - Castiglione F.
AU - Pappalardo F.
PY - 2013
SP - 617
EP - 625
DO - 10.5220/0004405706170625