Special Issue "Multiscale and Hybrid Modeling of the Living Systems"

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Biology".

Deadline for manuscript submissions: closed (31 October 2016)

Special Issue Editors

Guest Editor
Prof. Dr. Gennady Bocharov

Institute of Numerical Mathematics of the Russian Academy of Sciences, Gubkina Street 8, Moscow, Russian Federation
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Interests: data-driven modeling; system identification; mathematical immunology
Guest Editor
Prof. Dr. Olga Solovyova

Ural Federal University, Head of Laboratory, Institute of Immunology and Physiology, Ural Branch of Russian Academy o Sciences, Pervomayskaya 106, 620049 Yekaterinburg, Russian Federation
Website | E-Mail
Interests: mathematical physiology; biomechanics; cardiac computational models
Guest Editor
Prof. Dr. Vitaly Volpert

Directeur de recherche au CNRS, Institut Camille Jordan, University Lyon 1, 69622 Villeurbanne, France
Website | E-Mail
Interests: mathematical modeling in biology; multi-scale models; hybrid models

Special Issue Information

Dear Colleagues,

This Special Issue is intended to present recent advances and open problems in the development and computer implementation of high-resolution multi-parameter models, describing various levels of living systems organization. The relevant details of the experimental and mathematical techniques used for the quantitative characterization of the systems elements at different levels will be discussed.
Living systems are characterized by an enormous complexity of their structures, regulation, and dynamics. The mainstream approach to their analysis puts a strong emphasis on the acquisition of quantitative data and comprehensive measurements of a plethora of biological parameters. Nowadays it has become evident that, in order to gain a predictive understanding of the normal and pathological functioning of living systems, there is an urgent need of an efficient methodology for an information-rich, systems-based multiscale and hybrid modeling. The models which are developed to integrate a broad range of physical, chemical, biological phenomena with a large variation in their temporal and spatial scales represent a major challenge for numerical analysis and computational treatment. Advances in dynamic and global scale measurements of the system components at the gene-, cellular-, organ-, and whole organism-levels, and high resolution imaging technologies, should help to overcome the limitations of purely reductionist modeling approaches of the era preceding the development of systems biology. Our aim is to provide a comprehensive overview of the existing computational modeling approaches allowing one to include different scales into global models of living systems and enabling the identification of key targets to treat various diseases.

Prof. Dr. Gennady Bocharov
Prof. Dr. Olga Solovyova
Prof. Dr. Vitaly Volpert
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Living Systems
  • Integrative modeling
  • Multiscale models
  • Network models
  • Hybrid models
  • Systems Biology and Medicine
  • Computational methods

Published Papers (9 papers)

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Research

Open AccessArticle Scatter Search Applied to the Inference of a Development Gene Network
Computation 2017, 5(2), 22; doi:10.3390/computation5020022
Received: 10 March 2017 / Revised: 19 April 2017 / Accepted: 28 April 2017 / Published: 4 May 2017
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Abstract
Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods.
[...] Read more.
Efficient network inference is one of the challenges of current-day biology. Its application to the study of development has seen noteworthy success, yet a multicellular context, tissue growth, and cellular rearrangements impose additional computational costs and prohibit a wide application of current methods. Therefore, reducing computational cost and providing quick feedback at intermediate stages are desirable features for network inference. Here we propose a hybrid approach composed of two stages: exploration with scatter search and exploitation of intermediate solutions with low temperature simulated annealing. We test the approach on the well-understood process of early body plan development in flies, focusing on the gap gene network. We compare the hybrid approach to simulated annealing, a method of network inference with a proven track record. We find that scatter search performs well at exploring parameter space and that low temperature simulated annealing refines the intermediate results into excellent model fits. From this we conclude that for poorly-studied developmental systems, scatter search is a valuable tool for exploration and accelerates the elucidation of gene regulatory networks. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle Simplification of Reaction Networks, Confluence and Elementary Modes
Computation 2017, 5(1), 14; doi:10.3390/computation5010014
Received: 17 January 2017 / Accepted: 26 February 2017 / Published: 10 March 2017
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Abstract
Reaction networks can be simplified by eliminating linear intermediate species in partial steadystates. Inthispaper,westudythequestionwhetherthisrewriteprocedureisconfluent,so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We first show that confluence fails for the
[...] Read more.
Reaction networks can be simplified by eliminating linear intermediate species in partial steadystates. Inthispaper,westudythequestionwhetherthisrewriteprocedureisconfluent,so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We first show that confluence fails for the elimination of intermediates even without kinetics, if “dependent reactions” introduced by the simplification are not removed. This leads us to revising the simplification algorithm into a variant of the double description method for computing elementary modes, so that it keeps track of kinetic information. Folklore results on elementary modes imply the confluence of the revised simplification algorithm with respect to the network structure, i.e., the structure of fully simplified networks is unique. We show, however, that the kinetic rates assigned to the reactions may not be unique, and provide a biological example where two different simplified networks can be obtained. Finally, we give a criterion on the structure of the initial network that is sufficient to guarantee the confluence of both the structure and the kinetic rates. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle A Hybrid Computation Model to Describe the Progression of Multiple Myeloma and Its Intra-Clonal Heterogeneity
Computation 2017, 5(1), 16; doi:10.3390/computation5010016
Received: 18 October 2016 / Accepted: 5 March 2017 / Published: 10 March 2017
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Abstract
Multiplemyeloma(MM)isageneticallycomplexhematologicalcancerthatischaracterized by proliferation of malignant plasma cells in the bone marrow. MM evolves from the clonal premalignant disorder monoclonal gammopathy of unknown significance (MGUS) by sequential genetic changes involving many different genes, resulting in dysregulated growth of multiple clones of plasma cells. The
[...] Read more.
Multiplemyeloma(MM)isageneticallycomplexhematologicalcancerthatischaracterized by proliferation of malignant plasma cells in the bone marrow. MM evolves from the clonal premalignant disorder monoclonal gammopathy of unknown significance (MGUS) by sequential genetic changes involving many different genes, resulting in dysregulated growth of multiple clones of plasma cells. The migration, survival, and proliferation of these clones require the direct and indirect interactions with the non-hematopoietic cells of the bone marrow. We develop a hybrid discrete-continuous model of MM development from the MGUS stage. The discrete aspect of the modelisobservedatthecellularlevel: cellsarerepresentedasindividualobjectswhichmove,interact, divide, and die by apoptosis. Each of these actions is regulated by intracellular and extracellular processes as described by continuous models. The hybrid model consists of the following submodels that have been simplified from the much more complex state of evolving MM: cell motion due to chemotaxis, intracellular regulation of plasma cells, extracellular regulation in the bone marrow, and acquisition of mutations upon cell division. By extending a previous, simpler model in which the extracellular matrix was considered to be uniformly distributed, the new hybrid model provides a more accurate description in which cytokines are produced by the marrow microenvironment and consumed by the myeloma cells. The complex multiple genetic changes in MM cells and the numerous cell-cell and cytokine-mediated interactions between myeloma cells and their marrow microenviroment are simplified in the model such that four related but evolving MM clones can be studied as they compete for dominance in the setting of intraclonal heterogeneity. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle Multiscale CT-Based Computational Modeling of Alveolar Gas Exchange during Artificial Lung Ventilation, Cluster (Biot) and Periodic (Cheyne-Stokes) Breathings and Bronchial Asthma Attack
Computation 2017, 5(1), 11; doi:10.3390/computation5010011
Received: 31 October 2016 / Revised: 14 February 2017 / Accepted: 15 February 2017 / Published: 18 February 2017
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Abstract
An airflow in the first four generations of the tracheobronchial tree was simulated by the 1D model of incompressible fluid flow through the network of the elastic tubes coupled with 0D models of lumped alveolar components, which aggregates parts of the alveolar volume
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An airflow in the first four generations of the tracheobronchial tree was simulated by the 1D model of incompressible fluid flow through the network of the elastic tubes coupled with 0D models of lumped alveolar components, which aggregates parts of the alveolar volume and smaller airways, extended with convective transport model throughout the lung and alveolar components which were combined with the model of oxygen and carbon dioxide transport between the alveolar volume and the averaged blood compartment during pathological respiratory conditions. The novel features of this work are 1D reconstruction of the tracheobronchial tree structure on the basis of 3D segmentation of the computed tomography (CT) data; 1D−0D coupling of the models of 1D bronchial tube and 0D alveolar components; and the alveolar gas exchange model. The results of our simulations include mechanical ventilation, breathing patterns of severely ill patients with the cluster (Biot) and periodic (Cheyne-Stokes) respirations and bronchial asthma attack. The suitability of the proposed mathematical model was validated. Carbon dioxide elimination efficiency was analyzed in all these cases. In the future, these results might be integrated into research and practical studies aimed to design cyberbiological systems for remote real-time monitoring, classification, prediction of breathing patterns and alveolar gas exchange for patients with breathing problems. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle Towards a Multiscale Model of Acute HIV Infection
Computation 2017, 5(1), 6; doi:10.3390/computation5010006
Received: 31 October 2016 / Revised: 22 December 2016 / Accepted: 3 January 2017 / Published: 10 January 2017
Cited by 2 | PDF Full-text (1479 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Human Immunodeficiency Virus (HIV) infection of humans represents a complex biological system and a great challenge to public health. Novel approaches for the analysis and prediction of the infection dynamics based on a multi-scale integration of virus ontogeny and immune reactions are needed
[...] Read more.
Human Immunodeficiency Virus (HIV) infection of humans represents a complex biological system and a great challenge to public health. Novel approaches for the analysis and prediction of the infection dynamics based on a multi-scale integration of virus ontogeny and immune reactions are needed to deal with the systems’ complexity. The aim of our study is: (1) to formulate a multi-scale mathematical model of HIV infection; (2) to implement the model computationally following a hybrid approach; and (3) to calibrate the model by estimating the parameter values enabling one to reproduce the “standard” observed dynamics of HIV infection in blood during the acute phase of primary infection. The modeling approach integrates the processes of infection spread and immune responses in Lymph Nodes (LN) to that observed in blood. The spatio-temporal population dynamics of T lymphocytes in LN in response to HIV infection is governed by equations linking an intracellular regulation of the lymphocyte fate by intercellular cytokine fields. We describe the balance of proliferation, differentiation and death at a single cell level as a consequence of gene activation via multiple signaling pathways activated by IL-2, IFNa and FasL. Distinct activation thresholds are used in the model to relate different modes of cellular responses to the hierarchy of the relative levels of the cytokines. We specify a reference set of model parameter values for the fundamental processes in lymph nodes that ensures a reasonable agreement with viral load and CD4+ T cell dynamics in blood. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle Critical Issues in Modelling Lymph Node Physiology
Computation 2017, 5(1), 3; doi:10.3390/computation5010003
Received: 30 September 2016 / Revised: 7 December 2016 / Accepted: 12 December 2016 / Published: 24 December 2016
Cited by 1 | PDF Full-text (12486 KB) | HTML Full-text | XML Full-text
Abstract
In this study, we discuss critical issues in modelling the structure and function of lymph nodes (LNs), with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell
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In this study, we discuss critical issues in modelling the structure and function of lymph nodes (LNs), with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell zone, there are vascular networks which play a key role in the delivery of information to the inner parts of the LN, i.e., the conduit and blood microvascular networks. We propose object-oriented computational algorithms to model the 3D geometry of the fibroblastic reticular cell (FRC) network and the microvasculature. Assuming that a conduit cylinder is densely packed with collagen fibers, the computational flow study predicted that the diffusion should be a dominating process in mass transport than convective flow. The geometry models are used to analyze the lymph flow properties through the conduit network in unperturbed- and damaged states of the LN. The analysis predicts that elimination of up to 60%–90% of edges is required to stop the lymph flux. This result suggests a high degree of functional robustness of the network. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle A Mathematical Spline-Based Model of Cardiac Left Ventricle Anatomy and Morphology
Computation 2016, 4(4), 42; doi:10.3390/computation4040042
Received: 25 June 2016 / Revised: 19 October 2016 / Accepted: 21 October 2016 / Published: 27 October 2016
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Abstract
Computer simulation of normal and diseased human heart activity requires a 3D anatomical model of the myocardium, including myofibers. For clinical applications, such a model has to be constructed based on routine methods of cardiac visualization, such as sonography. Symmetrical models are shown
[...] Read more.
Computer simulation of normal and diseased human heart activity requires a 3D anatomical model of the myocardium, including myofibers. For clinical applications, such a model has to be constructed based on routine methods of cardiac visualization, such as sonography. Symmetrical models are shown to be too rigid, so an analytical non-symmetrical model with enough flexibility is necessary. Based on previously-made anatomical models of the left ventricle, we propose a new, much more flexible spline-based analytical model. The model is fully described and verified against DT-MRI data. We show a way to construct it on the basis of sonography data. To use this model in further physiological simulations, we propose a numerical method to utilize finite differences in solving the reaction-diffusion problem together with an example of scroll wave dynamics simulation. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessFeature PaperArticle A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection
Computation 2016, 4(4), 39; doi:10.3390/computation4040039
Received: 25 August 2016 / Revised: 3 October 2016 / Accepted: 7 October 2016 / Published: 21 October 2016
Cited by 4 | PDF Full-text (4594 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Tuberculosis (TB) is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB). The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs) is the formation of spherical structures, primarily in lungs,
[...] Read more.
Tuberculosis (TB) is a world-wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB). The pathologic hallmark of Mtb infection in humans and Non-Human Primates (NHPs) is the formation of spherical structures, primarily in lungs, called granulomas. Infection occurs after inhalation of bacteria into lungs, where resident antigen-presenting cells (APCs), take up bacteria and initiate the immune response to Mtb infection. APCs traffic from the site of infection (lung) to lung-draining lymph nodes (LNs) where they prime T cells to recognize Mtb. These T cells, circulating back through blood, migrate back to lungs to perform their immune effector functions. We have previously developed a hybrid agent-based model (ABM, labeled GranSim) describing in silico immune cell, bacterial (Mtb) and molecular behaviors during tuberculosis infection and recently linked that model to operate across three physiological compartments: lung (infection site where granulomas form), lung draining lymph node (LN, site of generation of adaptive immunity) and blood (a measurable compartment). Granuloma formation and function is captured by a spatio-temporal model (i.e., ABM), while LN and blood compartments represent temporal dynamics of the whole body in response to infection and are captured with ordinary differential equations (ODEs). In order to have a more mechanistic representation of APC trafficking from the lung to the lymph node, and to better capture antigen presentation in a draining LN, this current study incorporates the role of dendritic cells (DCs) in a computational fashion into GranSim. Results: The model was calibrated using experimental data from the lungs and blood of NHPs. The addition of DCs allowed us to investigate in greater detail mechanisms of recruitment, trafficking and antigen presentation and their role in tuberculosis infection. Conclusion: The main conclusion of this study is that early events after Mtb infection are critical to establishing a timely and effective response. Manipulating CD8+ and CD4+ T cell proliferation rates, as well as DC migration early on during infection can determine the difference between bacterial clearance vs. uncontrolled bacterial growth and dissemination. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Open AccessArticle Image Segmentation for Cardiovascular Biomedical Applications at Different Scales
Computation 2016, 4(3), 35; doi:10.3390/computation4030035
Received: 30 June 2016 / Revised: 27 August 2016 / Accepted: 5 September 2016 / Published: 15 September 2016
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Abstract
In this study, we present several image segmentation techniques for various image scales and modalities. We consider cellular-, organ-, and whole organism-levels of biological structures in cardiovascular applications. Several automatic segmentation techniques are presented and discussed in this work. The overall pipeline for
[...] Read more.
In this study, we present several image segmentation techniques for various image scales and modalities. We consider cellular-, organ-, and whole organism-levels of biological structures in cardiovascular applications. Several automatic segmentation techniques are presented and discussed in this work. The overall pipeline for reconstruction of biological structures consists of the following steps: image pre-processing, feature detection, initial mask generation, mask processing, and segmentation post-processing. Several examples of image segmentation are presented, including patient-specific abdominal tissues segmentation, vascular network identification and myocyte lipid droplet micro-structure reconstruction. Full article
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: The protective role of enhanced dendritic cells trafficking and antigen presentation in a computational hybrid model of tuberculosis infection
Author: Simeone Marino and Denise Kirschner
Abstract: Tuberculosis (TB) is a world wide health problem with approximately 2 billion people infected with Mycobacterium tuberculosis (Mtb, the causative bacterium of TB). The pathologic hallmark of Mtb infection in humans and non-human primates (NHP) is the formation of spherical structures, primarily in the lungs, called granulomas. Infection occurs after inhalation of the bacteria into the lungs, where resident antigen presenting cells (APCs), take them up and initiate the immune response to Mtb infection. Dendritic cells (DCs), professional APCs, traffic from the site of infection (lung) to lung-draining lymph nodes (LNs) where they prime T cells to recognize Mtb. These T cells, circulating through the blood system, eventually migrate back to the lung to perform their immune effector functions. We recently developed a hybrid agent-based model (ABM, labeled GranSim) describing in silico cellular (i.e., macrophages and T cells), bacterial (Mtb) and molecular signaling proteins dynamics during Mtb infection in 3 physiological compartments: lung (where granulomas form), draining lymph node (LN, site of generation of immunity) and blood (an easily measurable compartment). We capture single granuloma formation and function using a spatio-temporal model (i.e., ABM), while LN and blood compartments represent temporal dynamics of the whole body in response to infection. In this current study, to have a better representation of APC trafficking from the lung to the lymphatics, and to better capture antigen presentation in the draining LN, we include dendritic cells (DCs) into GranSim. The addition of DCs allowed us to investigate in greater detail mechanisms of recruitment, trafficking and antigen presentation between physiological compartments, as well as to identify potential DC immuno-protective roles during Mtb infection and granuloma formation.

Title: Reducing the computational footprint for parameter estimation of spatio-temporal patterning models with scatter search
Author: Anton Crombach et al.
Abstract: Network inference is one of the hard problems in biology today. This is especially the case for developmental biology, where a multicellular context creates computational challenges. As a result, network inference often requires high-performance computing facilities to perform rigorous fitting of parameters. Such facilities come at a cost of specific know-how, application forms and reports to justify computing hours, waiting times in execution queues, and occasionally simply at a cost of money. Single workstations in the office avoid all these issues, and ongoing computational advances both in hardware and search techniques warrant the re-asssessment of their usefulness in the context of network inference challenges.
Here we use the reverse engineering of the gap gene system in the fruit fly Drosophila melanogaster (and scuttle fly Megaselia abdita) as a benchmark to compare recent advances in search techniques. We compare our default methodology, simulated annealing, to a relatively novel method named scatter search. We find that scatter search on a single workstation is capable of generating comparable results to simulated annealing on a HPC facility.
We conclude that a rigorous tackling of medium-sized network inference problems in developmental biology is becoming feasible with "modest" current-day computing power available on the desktop.

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