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Symmetry
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Mathematical and Computational Approaches in Biology: Symmetry, Geometry and...
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Mathematical and Computational Approaches in Biology: Symmetry, Geometry and Conservation Laws

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Life Sciences".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 4076

Special Issue Editors

Dr. Federico Papa

E-Mail Website
Guest Editor
Institute for Systems Analysis and Computer Science “A. Ruberti”, National Research Council, 00185 Rome, Italy
Interests: mathematical modeling of biological systems; mathematical modeling and control of tumor growth and treatment; mathematical modeling of epidemics; systems biology; dynamical system identification and filtering; optimal control theory
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Pasquale Palumbo

E-Mail Website
Guest Editor
Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milan, Italy
Interests: mathematical modeling of biological systems; mathematical modeling and control of tumor growth and treatment; mathematical modeling of the glucose–insulin system and the artificial pancreas; mathematical modeling of epidemics; systems biology

Special Issue Information

Dear Colleagues,

Uncovering the laws and inner mechanisms of biology is a fascinating challenge for the scientific community. Mathematical and computational approaches play a fundamental role in this challenge, offering powerful methods and instruments for the analysis and comprehension of the unknown mechanisms that govern complex functions and phenomena. Mathematical modeling and numerical simulations, statistical analysis and bioinformatics allow us to describe the salient aspects and the governing laws of biological systems, whilst also elucidating the system behavior in time and space and evidencing symmetry, or symmetry breaking, in geometry and morphology. These methods also allow us to extract and maximize the information coming from the experimental data, thus offering instruments for unraveling the biological complexity and obtaining mechanistic insight. Moreover, mathematical and computational approaches allow us to reliably forecast the future evolution of the system or its response to exogenous perturbations, suggesting intervention strategies to efficiently, sometimes optimally, treat and control its behavior.

This Special Issue is looking for innovative contributions of experienced researchers in the field of mathematical modeling and bioinformatics applied to biology. Original research papers and reviews are welcome.

Submit your paper and select the Journal “Symmetry” and the Special Issue “Mathematical and Computational Approaches in Biology: Symmetry, Geometry and Conservation Laws” via: MDPI submission system. Our papers will be published on a rolling basis and we will be pleased to receive your submission once you have finished it.

Dr. Federico Papa
Prof. Dr. Pasquale Palumbo
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. Symmetry 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 2400 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

  • mathematical and computational biology
  • systems biology
  • biochemical networks
  • dynamical systems
  • structured population models
  • epidemic modeling
  • symmetry/asymmetry in biological patterns and structures
  • mathematical oncology

Published Papers (4 papers)

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Research

13 pages, 1465 KiB  
Article
Model-Based Regional Control with Anomalous Diffusion of Multi-Drug Combined Cancer Therapy for Volume Predictions
by Clara Mihaela Ionescu and Maria Ghita
Symmetry 2023, 15(1), 51; https://doi.org/10.3390/sym15010051 - 25 Dec 2022
Cited by 1 | Viewed by 996
Abstract
Symmetry breaking in the anatomical lung is triggered by tumorigenesis and disrupted by delivering single or multiple drugs to stop the progression of the tumor and treat cancer. In this study, a prior model of combined drug therapy is augmented to introduce tissue [...] Read more.
Symmetry breaking in the anatomical lung is triggered by tumorigenesis and disrupted by delivering single or multiple drugs to stop the progression of the tumor and treat cancer. In this study, a prior model of combined drug therapy is augmented to introduce tissue heterogeneity when the drug is applied in multi-drug therapy of lung cancer. Patient-related drug resistance and synergy are investigated as a function of diffusion intensity as drug molecules reach the tumor site. The results indicate that diffusion of drug molecules plays an important role next to other factors such as patient sensitivity to the drug and drug synergy effects. We conclude that the minimal model provides meaningful predictions on tumor growth at the intermediate mesoscale level. With such models at hand, it is now possible to employ model-based control algorithms to optimize the dose profiles in terms of time and amount. In this paper, we present a theoretical framework for control employing networked game theory optimality. Specific situations are discussed in terms of finding optimality at Nash equilibrium in relation to patient response and drug synergy effects. Full article
(This article belongs to the Special Issue Mathematical and Computational Approaches in Biology: Symmetry, Geometry and Conservation Laws)
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12 pages, 458 KiB  
Article
The Stochastic Approach for SIR Epidemic Models: Do They Help to Increase Information from Raw Data?
by Alessandro Borri, Pasquale Palumbo and Federico Papa
Symmetry 2022, 14(11), 2330; https://doi.org/10.3390/sym14112330 - 06 Nov 2022
Cited by 1 | Viewed by 1136
Abstract
The recent outbreak of COVID-19 underlined the need for a fast and trustworthy methodology to identify the features of a pandemic, whose early identification is of help for designing non-pharmaceutical interventions (including lockdown and social distancing) to limit the progression of the disease. [...] Read more.
The recent outbreak of COVID-19 underlined the need for a fast and trustworthy methodology to identify the features of a pandemic, whose early identification is of help for designing non-pharmaceutical interventions (including lockdown and social distancing) to limit the progression of the disease. A common approach in this context is the parameter identification from deterministic epidemic models, which, unfortunately, cannot take into account the inherent randomness of the epidemic phenomenon, especially in the initial stage; on the other hand, the use of raw data within the framework of a stochastic model is not straightforward. This note investigates the stochastic approach applied to a basic SIR (Susceptible, Infected, Recovered) epidemic model to enhance information from raw data generated in silico. The stochastic model consists of a Continuous-Time Markov Model, describing the epidemic outbreak in terms of stochastic discrete infection and recovery events in a given region, and where independent random paths are associated to different provinces of the same region, which are assumed to share the same set of model parameters. The estimation procedure is based on the building of a loss function that symmetrically weighs first-order and second-order moments, differently from the standard approach that considers a highly asymmetrical choice, exploiting only first-order moments. Instead, we opt for an innovative symmetrical identification approach which exploits both moments. The new approach is specifically proposed to enhance the statistical information content of the raw epidemiological data. Full article
(This article belongs to the Special Issue Mathematical and Computational Approaches in Biology: Symmetry, Geometry and Conservation Laws)
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12 pages, 1940 KiB  
Article
A Transcriptome- and Interactome-Based Analysis Identifies Repurposable Drugs for Human Breast Cancer Subtypes
by Federica Conte, Pasquale Sibilio, Giulia Fiscon and Paola Paci
Symmetry 2022, 14(11), 2230; https://doi.org/10.3390/sym14112230 - 24 Oct 2022
Cited by 4 | Viewed by 1272
Abstract
Breast cancer (BC) is a heterogeneous and complex disease characterized by different subtypes with distinct morphologies and clinical implications and for which new and effective treatment options are urgently demanded. The computational approaches recently developed for drug repurposing provide a very promising opportunity [...] Read more.
Breast cancer (BC) is a heterogeneous and complex disease characterized by different subtypes with distinct morphologies and clinical implications and for which new and effective treatment options are urgently demanded. The computational approaches recently developed for drug repurposing provide a very promising opportunity to offer tools that efficiently screen potential novel medical indications for various drugs that are already approved and used in clinical practice. Here, we started with disease-associated genes that were identified through a transcriptome-based analysis, which we used to predict potential repurposable drugs for various breast cancer subtypes by using an algorithm that we developed for drug repurposing called SAveRUNNER. Our findings were also in silico validated by performing a gene set enrichment analysis, which confirmed that most of the predicted repurposable drugs may have a potential treatment effect against breast cancer pathophenotypes. Full article
(This article belongs to the Special Issue Mathematical and Computational Approaches in Biology: Symmetry, Geometry and Conservation Laws)
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26 pages, 628 KiB  
Article
New Results and Open Questions for SIR-PH Epidemic Models with Linear Birth Rate, Loss of Immunity, Vaccination, and Disease and Vaccination Fatalities
by Florin Avram, Rim Adenane and Andrei Halanay
Symmetry 2022, 14(5), 995; https://doi.org/10.3390/sym14050995 - 12 May 2022
Cited by 2 | Viewed by 1444
Abstract
Our paper presents three new classes of models: SIR-PH, SIR-PH-FA, and SIR-PH-IA, and states two problems we would like to solve about them. Recall that deterministic mathematical epidemiology has one basic general law, the “R0 alternative” of Van den Driessche and [...] Read more.
Our paper presents three new classes of models: SIR-PH, SIR-PH-FA, and SIR-PH-IA, and states two problems we would like to solve about them. Recall that deterministic mathematical epidemiology has one basic general law, the “R0 alternative” of Van den Driessche and Watmough, which states that the local stability condition of the disease-free equilibrium may be expressed as R0<1, where R0 is the famous basic reproduction number, which also plays a major role in the theory of branching processes. The literature suggests that it is impossible to find general laws concerning the endemic points. However, it is quite common that 1. When R0>1, there exists a unique fixed endemic point, and 2. the endemic point is locally stable when R0>1. One would like to establish these properties for a large class of realistic epidemic models (and we do not include here epidemics without casualties). We have introduced recently a “simple” but broad class of “SIR-PH models” with varying populations, with the express purpose of establishing for these processes the two properties above. Since that seemed still hard, we have introduced a further class of “SIR-PH-FA” models, which may be interpreted as approximations for the SIR-PH models, and which include simpler models typically studied in the literature (with constant population, without loss of immunity, etc.). For this class, the first “endemic law” above is “almost established”, as explicit formulas for a unique endemic point are available, independently of the number of infectious compartments, and it only remains to check its belonging to the invariant domain. This may yet turn out to be always verified, but we have not been able to establish that. However, the second property, the sufficiency of R0>1 for the local stability of an endemic point, remains open even for SIR-PH-FA models, despite the numerous particular cases in which it was checked to hold (via Routh–Hurwitz time-onerous computations, or Lyapunov functions). The goal of our paper is to draw attention to the two open problems above, for the SIR-PH and SIR-PH-FA, and also for a second, more refined “intermediate approximation” SIR-PH-IA. We illustrate the current status-quo by presenting new results on a generalization of the SAIRS epidemic model. Full article
(This article belongs to the Special Issue Mathematical and Computational Approaches in Biology: Symmetry, Geometry and Conservation Laws)
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