51
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Castiglione F, Pappalardo F, Bianca C, Russo G, Motta S. Modeling biology spanning different scales: an open challenge. BIOMED RESEARCH INTERNATIONAL 2014; 2014:902545. [PMID: 25143952 PMCID: PMC4124842 DOI: 10.1155/2014/902545] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2014] [Accepted: 06/25/2014] [Indexed: 02/03/2023]
Abstract
It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.
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Affiliation(s)
- Filippo Castiglione
- Institute for Applied Mathematics, National Research Council of Italy, Rome, Italy
| | | | - Carlo Bianca
- Theoretical Physics of Condensed Matter, Sorbonne Universities, UPMC Univ Paris 6, 75252 Paris Cedex 05, France
- UMR 7600 LPTMC, CNRS, 75252 Paris Cedex 05, France
| | - Giulia Russo
- Department of Pharmaceutical Sciences, University of Catania, Catania, Italy
| | - Santo Motta
- Department of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy
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52
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Graudenzi A, Caravagna G, De Matteis G, Antoniotti M. Investigating the relation between stochastic differentiation, homeostasis and clonal expansion in intestinal crypts via multiscale modeling. PLoS One 2014; 9:e97272. [PMID: 24869488 PMCID: PMC4037186 DOI: 10.1371/journal.pone.0097272] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2013] [Accepted: 04/16/2014] [Indexed: 12/24/2022] Open
Abstract
Colorectal tumors originate and develop within intestinal crypts. Even though some of the essential phenomena that characterize crypt structure and dynamics have been effectively described in the past, the relation between the differentiation process and the overall crypt homeostasis is still only partially understood. We here investigate this relation and other important biological phenomena by introducing a novel multiscale model that combines a morphological description of the crypt with a gene regulation model: the emergent dynamical behavior of the underlying gene regulatory network drives cell growth and differentiation processes, linking the two distinct spatio-temporal levels. The model relies on a few a priori assumptions, yet accounting for several key processes related to crypt functioning, such as: dynamic gene activation patterns, stochastic differentiation, signaling pathways ruling cell adhesion properties, cell displacement, cell growth, mitosis, apoptosis and the presence of biological noise. We show that this modeling approach captures the major dynamical phenomena that characterize the regular physiology of crypts, such as cell sorting, coordinate migration, dynamic turnover, stem cell niche correct positioning and clonal expansion. All in all, the model suggests that the process of stochastic differentiation might be sufficient to drive the crypt to homeostasis, under certain crypt configurations. Besides, our approach allows to make precise quantitative inferences that, when possible, were matched to the current biological knowledge and it permits to investigate the role of gene-level perturbations, with reference to cancer development. We also remark the theoretical framework is general and may be applied to different tissues, organs or organisms.
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Affiliation(s)
- Alex Graudenzi
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- * E-mail:
| | - Giulio Caravagna
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
| | - Giovanni De Matteis
- Department of Mathematics and Information Sciences, Northumbria University, Newcastle, United Kingdom
| | - Marco Antoniotti
- Dept. of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
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53
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Cvijovic M, Almquist J, Hagmar J, Hohmann S, Kaltenbach HM, Klipp E, Krantz M, Mendes P, Nelander S, Nielsen J, Pagnani A, Przulj N, Raue A, Stelling J, Stoma S, Tobin F, Wodke JAH, Zecchina R, Jirstrand M. Bridging the gaps in systems biology. Mol Genet Genomics 2014; 289:727-34. [DOI: 10.1007/s00438-014-0843-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Accepted: 03/21/2014] [Indexed: 12/17/2022]
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54
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Groen D, Borgdorff J, Bona-Casas C, Hetherington J, Nash RW, Zasada SJ, Saverchenko I, Mamonski M, Kurowski K, Bernabeu MO, Hoekstra AG, Coveney PV. Flexible composition and execution of high performance, high fidelity multiscale biomedical simulations. Interface Focus 2014; 3:20120087. [PMID: 24427530 DOI: 10.1098/rsfs.2012.0087] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Multiscale simulations are essential in the biomedical domain to accurately model human physiology. We present a modular approach for designing, constructing and executing multiscale simulations on a wide range of resources, from laptops to petascale supercomputers, including combinations of these. Our work features two multiscale applications, in-stent restenosis and cerebrovascular bloodflow, which combine multiple existing single-scale applications to create a multiscale simulation. These applications can be efficiently coupled, deployed and executed on computers up to the largest (peta) scale, incurring a coupling overhead of 1-10% of the total execution time.
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Affiliation(s)
- D Groen
- Centre for Computational Science, University College London, UK
| | - J Borgdorff
- Section Computational Science, University of Amsterdam, The Netherlands
| | - C Bona-Casas
- Section Computational Science, University of Amsterdam, The Netherlands
| | - J Hetherington
- Centre for Computational Science, University College London, UK
| | - R W Nash
- Centre for Computational Science, University College London, UK
| | - S J Zasada
- Centre for Computational Science, University College London, UK
| | | | - M Mamonski
- Poznan Supercomputing and Networking Center, Poznan, Poland
| | - K Kurowski
- Poznan Supercomputing and Networking Center, Poznan, Poland
| | - M O Bernabeu
- Centre for Computational Science, University College London, UK
| | - A G Hoekstra
- Section Computational Science, University of Amsterdam, The Netherlands
| | - P V Coveney
- Centre for Computational Science, University College London, UK
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55
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Rabinovich AL, Lyubartsev AP. Computer simulation of lipid membranes: Methodology and achievements. POLYMER SCIENCE SERIES C 2013. [DOI: 10.1134/s1811238213070060] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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56
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Montes J, Gomez E, Merchán-Pérez A, DeFelipe J, Peña JM. A machine learning method for the prediction of receptor activation in the simulation of synapses. PLoS One 2013; 8:e68888. [PMID: 23894367 PMCID: PMC3720878 DOI: 10.1371/journal.pone.0068888] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2013] [Accepted: 06/01/2013] [Indexed: 11/18/2022] Open
Abstract
Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations.
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Affiliation(s)
- Jesus Montes
- Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain
| | - Elena Gomez
- Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain
| | - Angel Merchán-Pérez
- Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas, Madrid, Spain
| | - Jose-Maria Peña
- Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain
- * E-mail:
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Abstract
Wound healing in the pediatric patient is of utmost clinical and social importance because hypertrophic scarring can have aesthetic and psychological sequelae, from early childhood to late adolescence. Wound healing is a well-orchestrated reparative response affecting the damaged tissue at the cellular, tissue, organ, and system scales. Although tremendous progress has been made toward understanding wound healing at the individual temporal and spatial scales, its effects across the scales remain severely understudied and poorly understood. Here, we discuss the critical need for systems-based computational modeling of wound healing across the scales, from short-term to long-term and from small to large. We illustrate the state of the art in systems modeling by means of three key signaling mechanisms: oxygen tension-regulating angiogenesis and revascularization; transforming growth factor-β (TGF-β) kinetics controlling collagen deposition; and mechanical stretch stimulating cellular mitosis and extracellular matrix (ECM) remodeling. The complex network of biochemical and biomechanical signaling mechanisms and the multiscale character of the healing process make systems modeling an integral tool in exploring personalized strategies for wound repair. A better mechanistic understanding of wound healing in the pediatric patient could open new avenues in treating children with skin disorders such as birth defects, skin cancer, wounds, and burn injuries.
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Affiliation(s)
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA 94305,Department of Bioengineering, Stanford University, Stanford, CA 94305
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58
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Yang A. On the Common Conceptual and Computational Frameworks for Multiscale Modeling. Ind Eng Chem Res 2013. [DOI: 10.1021/ie303123s] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Affiliation(s)
- Aidong Yang
- Department of Chemical and Process
Engineering, Faculty
of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, U.K
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59
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Borgdorff J, Mamonski M, Bosak B, Groen D, Belgacem MB, Kurowski K, Hoekstra AG. Multiscale Computing with the Multiscale Modeling Library and Runtime Environment. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/j.procs.2013.05.275] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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60
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Baldazzi V, Bertin N, de Jong H, Génard M. Towards multiscale plant models: integrating cellular networks. TRENDS IN PLANT SCIENCE 2012; 17:728-36. [PMID: 22818768 DOI: 10.1016/j.tplants.2012.06.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2012] [Revised: 06/22/2012] [Accepted: 06/26/2012] [Indexed: 05/22/2023]
Abstract
One of the ambitions of 'crop systems biology' is to combine information from molecular biology with a broader view of plant development and growth. In the context of modeling, this calls for a multiscale perspective that focuses on the interplay between cellular and macroscopic studies. With this in mind, in this review we aim to draw attention to a panel of approaches that were developed in the context of systems biology and are used for analyzing and describing the behavior of cellular networks. Ultimately, insights obtained from these methods can be exploited to refine the description of plant processes, leading to integrated plant-cellular models.
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Affiliation(s)
- Valentina Baldazzi
- INRA, UR 1115 Plantes et Systèmes de Culture Horticoles, Domaine St Paul, Site Agroparc, F-84941 Avignon Cedex 9, France.
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61
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Baldazzi V, Bertin N, de Jong H, Génard M. Towards multiscale plant models: integrating cellular networks. TRENDS IN PLANT SCIENCE 2012. [PMID: 22818768 DOI: 10.1016/j.tplants.2012.06.012 [epub ahead of print]] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
One of the ambitions of 'crop systems biology' is to combine information from molecular biology with a broader view of plant development and growth. In the context of modeling, this calls for a multiscale perspective that focuses on the interplay between cellular and macroscopic studies. With this in mind, in this review we aim to draw attention to a panel of approaches that were developed in the context of systems biology and are used for analyzing and describing the behavior of cellular networks. Ultimately, insights obtained from these methods can be exploited to refine the description of plant processes, leading to integrated plant-cellular models.
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Affiliation(s)
- Valentina Baldazzi
- INRA, UR 1115 Plantes et Systèmes de Culture Horticoles, Domaine St Paul, Site Agroparc, F-84941 Avignon Cedex 9, France.
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62
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Abstract
BACKGROUND The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation? METHODS We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes. RESULTS Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes. CONCLUSION We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible.
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Affiliation(s)
- Ray Greek
- Americans For Medical Advancement (www.AFMA-curedisease.org), 2251 Refugio Rd, Goleta, CA, 93117, USA
| | - Mark J Rice
- Department of Anesthesiology, University of Florida College of Medicine, PO Box 100254, Gainesville, FL, 32610-0254, USA
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63
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Towards computer-aided multiscale modelling: A generic supporting environment for model realization and execution. Comput Chem Eng 2012. [DOI: 10.1016/j.compchemeng.2012.02.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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64
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Huang WH, Chui CK, Teoh SH, Chang SKY. A multiscale model for bioimpedance dispersion of liver tissue. IEEE Trans Biomed Eng 2012; 59:1593-7. [PMID: 22410954 DOI: 10.1109/tbme.2012.2190511] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Radio-frequency ablation (RFA) has been used in liver surgery to minimize blood loss during tissue division. However, the current RFA tissue division method lacks an effective way of determining the stoppage of blood flow. There is limitation on the current state-of-the-art laser Doppler flow sensor due to its small sensing area. A new technique was proposed to use bioimpedance for blood flow sensing. This paper discusses a new geometrical multiscale model of the liver bioimpedance incorporating blood flow impedance. This model establishes correlation between the physical tissue structure and bioimpedance measurement. The basic Debye structure within a multilevel framework is used in the model to account for bioimpedance dispersion. This dispersion is often explained by the Cole-Cole model that includes a constant phase element without physical explanation. Our model is able to account for reduced blood flow in its output with changes in permittivity in gamma dispersion that is mainly due to the polarization of water molecules. This study demonstrates the potential of a multiscale model in determining the stoppage of blood flow during surgery.
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Affiliation(s)
- W H Huang
- Department of Mechanical Engineering, National University of Singapore, 117576 Singapore.
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65
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Callebaut W. Scientific perspectivism: A philosopher of science's response to the challenge of big data biology. STUDIES IN HISTORY AND PHILOSOPHY OF BIOLOGICAL AND BIOMEDICAL SCIENCES 2012; 43:69-80. [PMID: 22326074 DOI: 10.1016/j.shpsc.2011.10.007] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Big data biology-bioinformatics, computational biology, systems biology (including 'omics'), and synthetic biology-raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data 'speak for themselves?' I discuss these issues by way of a reflection on Carl Woese's worry that "a society that permits biology to become an engineering discipline, that allows that science to slip into the role of changing the living world without trying to understand it, is a danger to itself." And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena.
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Affiliation(s)
- Werner Callebaut
- Konrad Lorenz Institute for Evolution and Cognition Research, Altenberg, Austria
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66
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Zhao Y, Jiang C, Yang A. Towards computer-aided multiscale modelling: An overarching methodology and support of conceptual modelling. Comput Chem Eng 2012. [DOI: 10.1016/j.compchemeng.2011.06.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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67
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Mattila J, Koikkalainen J, Virkki A, van Gils M, Lötjönen J. Design and application of a generic clinical decision support system for multiscale data. IEEE Trans Biomed Eng 2012; 59:234-40. [PMID: 21990325 PMCID: PMC6703550 DOI: 10.1109/tbme.2011.2170986] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Medical research and clinical practice are currently being redefined by the constantly increasing amounts of multiscale patient data. New methods are needed to translate them into knowledge that is applicable in healthcare. Multiscale modeling has emerged as a way to describe systems that are the source of experimental data. Usually, a multiscale model is built by combining distinct models of several scales, integrating, e.g., genetic, molecular, structural, and neuropsychological models into a composite representation. We present a novel generic clinical decision support system, which models a patient's disease state statistically from heterogeneous multiscale data. Its goal is to aid in diagnostic work by analyzing all available patient data and highlighting the relevant information to the clinician. The system is evaluated by applying it to several medical datasets and demonstrated by implementing a novel clinical decision support tool for early prediction of Alzheimer's disease.
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Affiliation(s)
- Jussi Mattila
- VTT Technical Research Centre of Finland, Tampere, Finland.
| | | | - Arho Virkki
- VTT Technical Research Centre of Finland, P.O. Box 1300, Finland
| | - Mark van Gils
- VTT Technical Research Centre of Finland, P.O. Box 1300, Finland
| | - Jyrki Lötjönen
- VTT Technical Research Centre of Finland, P.O. Box 1300, Finland
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68
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Lambrechts D, Schrooten J, Van de Putte T, Van Oosterwyck H. Computational Modeling of Mass Transport and Its Relation to Cell Behavior in Tissue Engineering Constructs. COMPUTATIONAL MODELING IN TISSUE ENGINEERING 2012. [DOI: 10.1007/8415_2012_139] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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69
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Ji S, Ford JC, Greenwald RM, Beckwith JG, Paulsen KD, Flashman LA, McAllister TW. Automated subject-specific, hexahedral mesh generation via image registration. FINITE ELEMENTS IN ANALYSIS AND DESIGN : THE INTERNATIONAL JOURNAL OF APPLIED FINITE ELEMENTS AND COMPUTER AIDED ENGINEERING 2011; 47:1178-1185. [PMID: 21731153 PMCID: PMC3124828 DOI: 10.1016/j.finel.2011.05.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Generating subject-specific, all-hexahedral meshes for finite element analysis continues to be of significant interest in biomechanical research communities. To date, most automated methods "morph" an existing atlas mesh to match with a subject anatomy, which usually result in degradation in mesh quality because of mesh distortion. We present an automated meshing technique that produces satisfactory mesh quality and accuracy without mesh repair. An atlas mesh is first developed using a script. A subject-specific mesh is generated with the same script after transforming the geometry into the atlas space following rigid image registration, and is transformed back into the subject space. By meshing the brain in 11 subjects, we demonstrate that the technique's performance is satisfactory in terms of both mesh quality (99.5% of elements had a scaled Jacobian >0.6 while <0.01% were between 0 and 0.2) and accuracy (average distance between mesh boundary and geometrical surface was 0.07 mm while <1% greater than 0.5mm). The combined computational cost for image registration and meshing was <4 min. Our results suggest that the technique is effective for generating subject-specific, all-hexahedral meshes and that it may be useful for meshing a variety of anatomical structures across different biomechanical research fields.
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Affiliation(s)
- Songbai Ji
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - James C. Ford
- Department of Psychiatry, Dartmouth Medical School, Lebanon, NH, USA
| | - Richard M. Greenwald
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
- Simbex, Lebanon, NH, USA
| | | | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
- Norris Cotton Cancer Center, Lebanon, NH, USA
| | - Laura A. Flashman
- Department of Psychiatry, Dartmouth Medical School, Lebanon, NH, USA
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70
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Qu Z, Garfinkel A, Weiss JN, Nivala M. Multi-scale modeling in biology: how to bridge the gaps between scales? PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2011; 107:21-31. [PMID: 21704063 DOI: 10.1016/j.pbiomolbio.2011.06.004] [Citation(s) in RCA: 95] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2011] [Accepted: 06/11/2011] [Indexed: 11/25/2022]
Abstract
Human physiological functions are regulated across many orders of magnitude in space and time. Integrating the information and dynamics from one scale to another is critical for the understanding of human physiology and the treatment of diseases. Multi-scale modeling, as a computational approach, has been widely adopted by researchers in computational and systems biology. A key unsolved issue is how to represent appropriately the dynamical behaviors of a high-dimensional model of a lower scale by a low-dimensional model of a higher scale, so that it can be used to investigate complex dynamical behaviors at even higher scales of integration. In the article, we first review the widely-used different modeling methodologies and their applications at different scales. We then discuss the gaps between different modeling methodologies and between scales, and discuss potential methods for bridging the gaps between scales.
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Affiliation(s)
- Zhilin Qu
- Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.
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71
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Reumann M, Fitch BG, Rayshubskiy A, Pitman MC, Rice JJ. Orthogonal recursive bisection as data decomposition strategy for massively parallel cardiac simulations. BIOMED ENG-BIOMED TE 2011; 56:129-45. [PMID: 21657987 DOI: 10.1515/bmt.2011.100] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We present the orthogonal recursive bisection algorithm that hierarchically segments the anatomical model structure into subvolumes that are distributed to cores. The anatomy is derived from the Visible Human Project, with electrophysiology based on the FitzHugh-Nagumo (FHN) and ten Tusscher (TT04) models with monodomain diffusion. Benchmark simulations with up to 16,384 and 32,768 cores on IBM Blue Gene/P and L supercomputers for both FHN and TT04 results show good load balancing with almost perfect speedup factors that are close to linear with the number of cores. Hence, strong scaling is demonstrated. With 32,768 cores, a 1000 ms simulation of full heart beat requires about 6.5 min of wall clock time for a simulation of the FHN model. For the largest machine partitions, the simulations execute at a rate of 0.548 s (BG/P) and 0.394 s (BG/L) of wall clock time per 1 ms of simulation time. To our knowledge, these simulations show strong scaling to substantially higher numbers of cores than reported previously for organ-level simulation of the heart, thus significantly reducing run times. The ability to reduce runtimes could play a critical role in enabling wider use of cardiac models in research and clinical applications.
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Affiliation(s)
- Matthias Reumann
- IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, USA.
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72
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Díaz-Zuccarini V, Pichardo-Almarza C. On the formalization of multi-scale and multi-science processes for integrative biology. Interface Focus 2011; 1:426-37. [PMID: 22670211 DOI: 10.1098/rsfs.2010.0038] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2010] [Accepted: 03/02/2011] [Indexed: 11/12/2022] Open
Abstract
The aim of this work is to introduce the general concept of 'Bond Graph' (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the 'elements' of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The 'effort' and 'flow' variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view.
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Affiliation(s)
- Vanessa Díaz-Zuccarini
- Department of Mechanical Engineering , University College London , Torrington Place, London WC1E 7JE , UK
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73
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Yang JH, Saucerman JJ. Computational models reduce complexity and accelerate insight into cardiac signaling networks. Circ Res 2011; 108:85-97. [PMID: 21212391 DOI: 10.1161/circresaha.110.223602] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Cardiac signaling networks exhibit considerable complexity in size and connectivity. The intrinsic complexity of these networks complicates the interpretation of experimental findings. This motivates new methods for investigating the mechanisms regulating cardiac signaling networks and the consequences these networks have on cardiac physiology and disease. Next-generation experimental techniques are also generating a wealth of genomic and proteomic data that can be difficult to analyze or interpret. Computational models are poised to play a key role in addressing these challenges. Computational models have a long history in contributing to the understanding of cardiac physiology and are useful for identifying biological mechanisms, inferring multiscale consequences to cell signaling activities and reducing the complexity of large data sets. Models also integrate well with experimental studies to explain experimental observations and generate new hypotheses. Here, we review the contributions computational modeling approaches have made to the analysis of cardiac signaling networks and forecast opportunities for computational models to accelerate cardiac signaling research.
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Affiliation(s)
- Jason H Yang
- Department of Biomedical Engineering, Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, 22908, USA
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74
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Dada JO, Mendes P. Multi-scale modelling and simulation in systems biology. Integr Biol (Camb) 2011; 3:86-96. [DOI: 10.1039/c0ib00075b] [Citation(s) in RCA: 129] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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75
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Schrattenholz A, Groebe K, Soskic V. Systems biology approaches and tools for analysis of interactomes and multi-target drugs. Methods Mol Biol 2010; 662:29-58. [PMID: 20824465 DOI: 10.1007/978-1-60761-800-3_2] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.
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76
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Shah I, Wambaugh J. Virtual tissues in toxicology. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2010; 13:314-328. [PMID: 20574905 DOI: 10.1080/10937404.2010.483948] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
New approaches are vital for efficiently evaluating human health risk of thousands of chemicals in commerce. In vitro models offer a high-throughput approach for assaying chemical-induced molecular and cellular changes; however, bridging these perturbations to in vivo effects across chemicals, dose, time, and species remains challenging. Technological advances in multiresolution imaging and multiscale simulation are making it feasible to reconstruct tissues in silico. In toxicology, these "virtual" tissues (VT) aim to predict histopathological outcomes from alterations of cellular phenotypes that are controlled by chemical-induced perturbations in molecular pathways. The behaviors of thousands of heterogeneous cells in tissues are simulated discretely using agent-based modeling (ABM), in which computational "agents" mimic cell interactions and cellular responses to the microenvironment. The behavior of agents is constrained by physical laws and biological rules derived from experimental evidence. VT extend compartmental physiologic models to simulate both acute insults as well as the chronic effects of low-dose exposure. Furthermore, agent behavior can encode the logic of signaling and genetic regulatory networks to evaluate the role of different pathways in chemical-induced injury. To extrapolate toxicity across species, chemicals, and doses, VT require four main components: (a) organization of prior knowledge on physiologic events to define the mechanistic rules for agent behavior, (b) knowledge on key chemical-induced molecular effects, including activation of stress sensors and changes in molecular pathways that alter the cellular phenotype, (c) multiresolution quantitative and qualitative analysis of histologic data to characterize and measure chemical-, dose-, and time-dependent physiologic events, and (d) multiscale, spatiotemporal simulation frameworks to effectively calibrate and evaluate VT using experimental data. This investigation presents the motivation, implementation, and application of VT with examples from hepatotoxicity and carcinogenesis.
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Affiliation(s)
- Imran Shah
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
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77
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Neal ML, Kerckhoffs R. Current progress in patient-specific modeling. Brief Bioinform 2010; 11:111-26. [PMID: 19955236 PMCID: PMC2810113 DOI: 10.1093/bib/bbp049] [Citation(s) in RCA: 99] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2009] [Revised: 09/20/2009] [Indexed: 11/13/2022] Open
Abstract
We present a survey of recent advancements in the emerging field of patient-specific modeling (PSM). Researchers in this field are currently simulating a wide variety of tissue and organ dynamics to address challenges in various clinical domains. The majority of this research employs three-dimensional, image-based modeling techniques. Recent PSM publications mostly represent feasibility or preliminary validation studies on modeling technologies, and these systems will require further clinical validation and usability testing before they can become a standard of care. We anticipate that with further testing and research, PSM-derived technologies will eventually become valuable, versatile clinical tools.
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Affiliation(s)
- Maxwell Lewis Neal
- Division of Biomedical and Health Informatics, University of Washington, USA
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78
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Sloot PMA, Hoekstra AG. Multi-scale modelling in computational biomedicine. Brief Bioinform 2009; 11:142-52. [PMID: 20028713 DOI: 10.1093/bib/bbp038] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The inherent complexity of biomedical systems is well recognized; they are multi-scale, multi-science systems, bridging a wide range of temporal and spatial scales. This article reviews the currently emerging field of multi-scale modelling in computational biomedicine. Many exciting multi-scale models exist or are under development. However, an underpinning multi-scale modelling methodology seems to be missing. We propose a direction that complements the classic dynamical systems approach and introduce two distinct case studies, transmission of resistance in human immunodeficiency virus spreading and in-stent restenosis in coronary artery disease.
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Affiliation(s)
- Peter M A Sloot
- Computational Science, Faculty of Science, University of Amsterdam, Kruislaan 403, 1098 SJ Amsterdam, The Netherlands.
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79
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de Graaf AA, Freidig AP, De Roos B, Jamshidi N, Heinemann M, Rullmann JAC, Hall KD, Adiels M, van Ommen B. Nutritional systems biology modeling: from molecular mechanisms to physiology. PLoS Comput Biol 2009; 5:e1000554. [PMID: 19956660 PMCID: PMC2777333 DOI: 10.1371/journal.pcbi.1000554] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a "middle-out" strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from "-omics" signatures are identified as key elements of a successful systems biology modeling approach in nutrition research--one that integrates physiological mechanisms and data at multiple space and time scales.
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80
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81
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Namas R, Ghuma A, Hermus L, Zamora R, Okonkwo DO, Billiar TR, Vodovotz Y. The acute inflammatory response in trauma / hemorrhage and traumatic brain injury: current state and emerging prospects. Libyan J Med 2009; 4:97-103. [PMID: 21483522 PMCID: PMC3066737 DOI: 10.4176/090325] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Traumatic injury/hemorrhagic shock (T/HS) elicits an acute inflammatory response that may result in death. Inflammation describes a coordinated series of molecular, cellular, tissue, organ, and systemic responses that drive the pathology of various diseases including T/HS and traumatic brain injury (TBI). Inflammation is a finely tuned, dynamic, highly-regulated process that is not inherently detrimental, but rather required for immune surveillance, optimal post-injury tissue repair, and regeneration. The inflammatory response is driven by cytokines and chemokines and is partially propagated by damaged tissue-derived products (Damage-associated Molecular Patterns; DAMP's). DAMPs perpetuate inflammation through the release of pro-inflammatory cytokines, but may also inhibit anti-inflammatory cytokines. Various animal models of T/HS in mice, rats, pigs, dogs, and non-human primates have been utilized in an attempt to move from bench to bedside. Novel approaches, including those from the field of systems biology, may yield therapeutic breakthroughs in T/HS and TBI in the near future.
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82
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Qutub AA, Mac Gabhann F, Karagiannis ED, Vempati P, Popel AS. Multiscale models of angiogenesis. ACTA ACUST UNITED AC 2009; 28:14-31. [PMID: 19349248 DOI: 10.1109/memb.2009.931791] [Citation(s) in RCA: 102] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Vascular disease, cancer, stroke, neurodegeneration, diabetes, inflammation, asthma, obesity, arthritis--the list of conditions that involve angiogenesis reads like main chapters in a book on pathology. Angiogenesis, the growth of capillaries from preexisting vessels, also occurs in normal physiology, in response to exercise or in the process of wound healing.Why and when is angiogenesis prevalent? What controls the process? How can we intelligently control it? These are the key questions driving researchers in fields as diverse as cell biology, oncology, cardiology, neurology, biomathematics, systems biology, and biomedical engineering. As bioengineers, we approach angiogenesis as a complex, interconnected system of events occurring in sequence and in parallel, on multiple levels, triggered by a main stimulus, e.g., hypoxia.
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Affiliation(s)
- Amina A Qutub
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA.
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83
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Xu ZL, Shen YD, Beier RC, Yang JY, Lei HT, Wang H, Sun YM. Application of computer-assisted molecular modeling for immunoassay of low molecular weight food contaminants: A review. Anal Chim Acta 2009; 647:125-36. [DOI: 10.1016/j.aca.2009.06.003] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2009] [Revised: 05/30/2009] [Accepted: 06/02/2009] [Indexed: 10/20/2022]
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Lacroix D, Planell JA, Prendergast PJ. Computer-aided design and finite-element modelling of biomaterial scaffolds for bone tissue engineering. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2009; 367:1993-2009. [PMID: 19380322 DOI: 10.1098/rsta.2009.0024] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Scaffold biomaterials for tissue engineering can be produced in many different ways depending on the applications and the materials used. Most research into new biomaterials is based on an experimental trial-and-error approach that limits the possibility of making many variations to a single material and studying its interaction with its surroundings. Instead, computer simulation applied to tissue engineering can offer a more exhaustive approach to test and screen out biomaterials. In this paper, a review of the current approach in biomaterials designed through computer-aided design (CAD) and through finite-element modelling is given. First we review the approach used in tissue engineering in the development of scaffolds and the interactions existing between biomaterials, cells and mechanical stimuli. Then, scaffold fabrication through CAD is presented and characterization of existing scaffolds through computed images is reviewed. Several case studies of finite-element studies in tissue engineering show the usefulness of computer simulations in determining the mechanical environment of cells when seeded into a scaffold and the proper design of the geometry and stiffness of the scaffold. This creates a need for more advanced studies that include aspects of mechanobiology in tissue engineering in order to be able to predict over time the growth and differentiation of tissues within scaffolds. Finally, current perspectives indicate that more efforts need to be put into the development of such advanced studies, with the removal of technical limitations such as computer power and the inclusion of more accurate biological and genetic processes into the developed algorithms.
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Affiliation(s)
- Damien Lacroix
- Institute for Bioengineering of Catalonia, 08028 Barcelona, Spain.
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85
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Walker DC, Southgate J. The virtual cell--a candidate co-ordinator for 'middle-out' modelling of biological systems. Brief Bioinform 2009; 10:450-61. [PMID: 19293250 DOI: 10.1093/bib/bbp010] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Understanding the functioning of biological systems depends on tackling complexity spanning spatial scales from genome to organ to whole organism. The basic unit of life, the cell, acts to co-ordinate information received across these scales and processes the myriad of signals to produce an integrated cellular response. Cells interact with and respond to other cells through direct or indirect contact, resulting in emergent structure and function of tissues and organs. Systems biology has traditionally used either a 'top-down' or 'bottom-up' approach. However, neither approach takes account of heterogeneity or 'noise', which is an inherent feature of cellular behaviour and may have significant impact on system level behaviour. We review existing approaches to modelling that use cellular automata or agent-based methodologies, where individual cells are represented as equivalent virtual entities governed by simple rules. These paradigms allow a direct one-to-one mapping between real and virtual cells that can be exploited in terms of acquiring parameters from experimental systems, or for model validation. Such models are inherently extensible and can be integrated with other modelling modalities (e.g. partial or ordinary differential equations) to model multi-scale phenomena. Alternatively, hierarchical agent models may be used to explore the functions of biological systems across temporal and spatial scales. This review examines individual-based models and the application of the paradigm to explore multi-scale phenomena in biology. In so doing, it demonstrates how cellular-based models have begun to play an important role in the development of 'middle-out' models, but with considerable potential for future development.
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Affiliation(s)
- Dawn C Walker
- Department of Computer Science at the University of Sheffield
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Loewe L. A framework for evolutionary systems biology. BMC SYSTEMS BIOLOGY 2009; 3:27. [PMID: 19239699 PMCID: PMC2663779 DOI: 10.1186/1752-0509-3-27] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2008] [Accepted: 02/24/2009] [Indexed: 12/02/2022]
Abstract
BACKGROUND Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. RESULTS Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. CONCLUSION EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.
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Affiliation(s)
- Laurence Loewe
- Centre for Systems Biology at Edinburgh, The University of Edinburgh, Edinburgh, Scotland, UK.
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88
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Caiazzo A, Evans D, Falcone JL, Hegewald J, Lorenz E, Stahl B, Wang D, Bernsdorf J, Chopard B, Gunn J, Hose R, Krafczyk M, Lawford P, Smallwood R, Walker D, Hoekstra AG. Towards a Complex Automata Multiscale Model of In-Stent Restenosis. LECTURE NOTES IN COMPUTER SCIENCE 2009. [DOI: 10.1007/978-3-642-01970-8_70] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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89
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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. [DOI: 10.1016/j.mbs.2008.10.001] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2008] [Revised: 09/02/2008] [Accepted: 10/02/2008] [Indexed: 12/12/2022]
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90
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Reumann M, Gurev V, Rice JJ. Computational modeling of cardiac disease: potential for personalized medicine. Per Med 2009; 6:45-66. [DOI: 10.2217/17410541.6.1.45] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Cardiovascular diseases are leading causes of death, reduce life quality and consume almost half a trillion dollars in healthcare expenses in the USA alone. Cardiac modeling and simulation technologies hold promise as important tools to improve cardiac care and are already in use to elucidate the fundamental mechanisms of cardiac physiology and pathophysiology. However, the emphasis has been on simulating average or exemplar cases. This report describes two classes of cardiac modeling efforts. First, electrophysiological models of channelopathies simulate the altered electrical activity that is thought to promote arrhythmias. Second, electromechanical models attempt to capture both the electrophysiological and mechanical aspects of heart function. One goal of the community is to develop models with sufficient patient customization to assist in personalized treatment planning. Some model aspects can be customized with existing data collection techniques to more closely represent individual patients while other model aspects will likely remain based on generic data. Despite important challenges, cardiac models hold promise to be important enablers of personalized medicine.
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Affiliation(s)
- Matthias Reumann
- Functional Genomics and Systems Biology, IBM T.J. Watson Research Center, PO Box 218, Yorktown Heights, NY 10598, USA
| | - Viatcheslav Gurev
- Department of Biomedical Engineering and Institute for Computational Medicine, The Johns Hopkins University, MD, USA
| | - John Jeremy Rice
- Functional Genomics and Systems Biology, IBM T.J. Watson Research Center, PO Box 218, Yorktown Heights, NY 10598, USA
- Department of Biomedical Engineering and Institute for Computational Medicine, The Johns Hopkins University, MD, USA
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91
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Saraniti M. Artificial cells: Designing biomimetic nanomachines. NATURE NANOTECHNOLOGY 2008; 3:647-648. [PMID: 18989327 DOI: 10.1038/nnano.2008.327] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
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