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Bioengineering
Special Issues
Role of Computational Methods for Living Systems at Different Scales
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Role of Computational Methods for Living Systems at Different Scales

A special issue of Bioengineering (ISSN 2306-5354).

Deadline for manuscript submissions: 20 February 2025 | Viewed by 5887

Special Issue Editors

Dr. Francesco Montefusco

E-Mail Website
Guest Editor
Department of Economics, Law, Cybersecurity, and Sports Sciences, University of Naples Parthenope, Nola, NA, Italy
Interests: systems and synthetic biology; modeling; analysis; identification; design and control of biological systems; mathematical modeling for excitable cells
Dr. Anna Procopio

E-Mail Website
Guest Editor
Department of Experimental and Clinical Medicine, Biomechatronics Lab, Università degli Studi Magna Gaecia, 88100 Catanzaro, Italy
Interests: systems biology; mathematical modeling; parameters optimization; model validation; bioengineering; medical data; health-care

Special Issue Information

Dear Colleagues,

In this Special Issue, we will highlight the importance of devising computational methods to better understand the functioning of living systems at different scales, from subcellular and cellular systems to organisms, populations, and even ecosystems.

In general, these systems are characterized by a high level of complexity, displaying strongly nonlinear and largely uncertain dynamics. These features represent a significant challenge in the development of new tools, methods, and appropriate frameworks for such systems.

Mathematical modeling, dynamical systems, control theory and optimization, and statistical analysis are examples of effective tools to be exploited, e.g., for describing complex biological systems, understanding and identifying their characteristics, making predictions, and controlling their behavior. Here, we will consider research or review papers that tackle these issues.

Topics of interest include but are not limited to the following:

  • The study of biochemical and biological processes at all scales, including modeling, analysis, identification, control, and design of such systems, with applications to systems and synthetic biology;
  • Modeling and applications in population biology, ecology and epidemiology, e.g., to investigate the dynamical behavior of infectious diseases and to develop control strategies to contain their spread;
  • Computational tools for biomedical systems, e.g., for designing and analyzing novel therapeutical approaches and healthcare monitoring.

Dr. Francesco Montefusco
Dr. Anna Procopio
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 submissions that pass pre-check are 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. Bioengineering is an international peer-reviewed open access monthly 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 2700 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

12 pages, 339 KiB  
Article
Structural Identifiability and Observability of Microbial Community Models
by Sandra Díaz-Seoane, Elena Sellán and Alejandro F. Villaverde
Bioengineering 2023, 10(4), 483; https://doi.org/10.3390/bioengineering10040483 - 17 Apr 2023
Viewed by 1668
Abstract
Biological communities are populations of various species interacting in a common location. Microbial communities, which are formed by microorganisms, are ubiquitous in nature and are increasingly used in biotechnological and biomedical applications. They are nonlinear systems whose dynamics can be accurately described by [...] Read more.
Biological communities are populations of various species interacting in a common location. Microbial communities, which are formed by microorganisms, are ubiquitous in nature and are increasingly used in biotechnological and biomedical applications. They are nonlinear systems whose dynamics can be accurately described by models of ordinary differential equations (ODEs). A number of ODE models have been proposed to describe microbial communities. However, the structural identifiability and observability of most of them—that is, the theoretical possibility of inferring their parameters and internal states by observing their output—have not been determined yet. It is important to establish whether a model possesses these properties, because, in their absence, the ability of a model to make reliable predictions may be compromised. Hence, in this paper, we analyse these properties for the main families of microbial community models. We consider several dimensions and measurements; overall, we analyse more than a hundred different configurations. We find that some of them are fully identifiable and observable, but a number of cases are structurally unidentifiable and/or unobservable under typical experimental conditions. Our results help in deciding which modelling frameworks may be used for a given purpose in this emerging area, and which ones should be avoided. Full article
(This article belongs to the Special Issue Role of Computational Methods for Living Systems at Different Scales)
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31 pages, 4385 KiB  
Article
A Theoretical Framework for Implementable Nucleic Acids Feedback Systems
by Nuno M. G. Paulino, Mathias Foo, Tom F. A. de Greef, Jongmin Kim and Declan G. Bates
Bioengineering 2023, 10(4), 466; https://doi.org/10.3390/bioengineering10040466 - 12 Apr 2023
Viewed by 1734
Abstract
Chemical reaction networks can be utilised as basic components for nucleic acid feedback control systems’ design for Synthetic Biology application. DNA hybridisation and programmed strand-displacement reactions are effective primitives for implementation. However, the experimental validation and scale-up of nucleic acid control systems are [...] Read more.
Chemical reaction networks can be utilised as basic components for nucleic acid feedback control systems’ design for Synthetic Biology application. DNA hybridisation and programmed strand-displacement reactions are effective primitives for implementation. However, the experimental validation and scale-up of nucleic acid control systems are still considerably falling behind their theoretical designs. To aid with the progress heading into experimental implementations, we provide here chemical reaction networks that represent two fundamental classes of linear controllers: integral and static negative state feedback. We reduced the complexity of the networks by finding designs with fewer reactions and chemical species, to take account of the limits of current experimental capabilities and mitigate issues pertaining to crosstalk and leakage, along with toehold sequence design. The supplied control circuits are quintessential candidates for the first experimental validations of nucleic acid controllers, since they have a number of parameters, species, and reactions small enough for viable experimentation with current technical capabilities, but still represent challenging feedback control systems. They are also well suited to further theoretical analysis to verify results on the stability, performance, and robustness of this important new class of control systems. Full article
(This article belongs to the Special Issue Role of Computational Methods for Living Systems at Different Scales)
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15 pages, 3312 KiB  
Article
Analytical Models of Intra- and Extratumoral Cell Interactions at Avascular Stage of Growth in the Presence of Targeted Chemotherapy
by Evgeniia Lavrenteva, Constantinos Theodoropoulos and Michael Binns
Bioengineering 2023, 10(3), 385; https://doi.org/10.3390/bioengineering10030385 - 21 Mar 2023
Viewed by 1657
Abstract
In this study, we propose a set of nonlinear differential equations to model the dynamic growth of avascular stage tumors, considering nutrient supply from underlying tissue, innate immune response, contact inhibition of cell migration, and interactions with a chemotherapeutic agent. The model has [...] Read more.
In this study, we propose a set of nonlinear differential equations to model the dynamic growth of avascular stage tumors, considering nutrient supply from underlying tissue, innate immune response, contact inhibition of cell migration, and interactions with a chemotherapeutic agent. The model has been validated against available experimental data from the literature for tumor growth. We assume that the size of the modeled tumor is already detectable, and it represents all clinically observed existent cell populations; initial conditions are selected accordingly. Numerical results indicate that the tumor size and regression significantly depend on the strength of the host immune system. The effect of chemotherapy is investigated, not only within the malignancy, but also in terms of the responding immune cells and healthy tissue in the vicinity of a tumor. Full article
(This article belongs to the Special Issue Role of Computational Methods for Living Systems at Different Scales)
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