Stochastic Models and Experiments in Ecology and Biology

Topic Information

Dear Colleagues,

Living systems are characterised by the emergence of dynamical patterns within a wide range of spatial and temporal scales. Self-organized behaviors are observed in large communities of microscopic components—such as neural oscillations and gene network activity—as well as in ecological communities. Such regularities are deemed to be universal; namely, they depend on general mechanisms that are independent of the fine details that define the system. Understanding the emergent behaviour of such complex systems naturally leads us to consider mathematical models that encapsulate key features, whilst neglecting inessential complications. Therefore, complexity and self-organization arise on a macroscopic scale from the dynamics of these individual components, which evolve because of coupling terms. Within this scenario, probability theory and statistical mechanics play a crucial role in identifying models and explaining patterns.

The aim of this conference is to bring together scientists with different backgrounds (mathematics, biology, physics and computer science, theoreticians along with experimentalists), interested in macroecology, microbial ecology and evolutionary biology, to discuss important and recent research topics in these areas as well as exchange methods and ideas. The style of the conference will purposely be informal so as to encourage discussions.

Dr. Sandro Azaele
Dr. Samir Simon Suweis

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Life life	3.2	4.3	2011	17.8 Days	CHF 2600
Entropy entropy	2.1	4.9	1999	22.3 Days	CHF 2600

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Published Papers (7 papers)

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12 pages, 742 KiB  

Open AccessArticle

Finite-Time Stochastic Stability Analysis of Permanent Magnet Synchronous Motors with Noise Perturbation

by Caoyuan Ma, Hongjun Shi, Pingping Nie and Jiaming Wu

Entropy 2022, 24(6), 791; https://doi.org/10.3390/e24060791 - 6 Jun 2022

Cited by 4 | Viewed by 1962

Abstract

In this paper, we study the finite-time stability of permanent magnet synchronous motors (PMSMs) with noise perturbation. To eliminate the chaos in a PMSM and allow it to reach a steady state more quickly within a finite time, we propose a novel adaptive [...] Read more.

In this paper, we study the finite-time stability of permanent magnet synchronous motors (PMSMs) with noise perturbation. To eliminate the chaos in a PMSM and allow it to reach a steady state more quickly within a finite time, we propose a novel adaptive controller based on finite-time control theory. Finite-time stability implies optimal convergence time and better robustness. Finally, numerical simulations are performed to demonstrate the effectiveness and feasibility of our new results. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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13 pages, 3900 KiB  

Open AccessArticle

Use of 6 Nucleotide Length Words to Study the Complexity of Gene Sequences from Different Organisms

by Eugene Korotkov, Konstantin Zaytsev and Alexey Fedorov

Entropy 2022, 24(5), 632; https://doi.org/10.3390/e24050632 - 30 Apr 2022

Cited by 2 | Viewed by 2023

Abstract

In this paper, we attempted to find a relation between bacteria living conditions and their genome algorithmic complexity. We developed a probabilistic mathematical method for the evaluation of k-words (6 bases length) occurrence irregularity in bacterial gene coding sequences. For this, the coding [...] Read more.

In this paper, we attempted to find a relation between bacteria living conditions and their genome algorithmic complexity. We developed a probabilistic mathematical method for the evaluation of k-words (6 bases length) occurrence irregularity in bacterial gene coding sequences. For this, the coding sequences from different bacterial genomes were analyzed and as an index of k-words occurrence irregularity, we used $W$, which has a distribution similar to normal. The research results for bacterial genomes show that they can be divided into two uneven groups. First, the smaller one has W in the interval from 170 to 475, while for the second it is from 475 to 875. Plants, metazoan and virus genomes also have W in the same interval as the first bacterial group. We suggested that second bacterial group coding sequences are much less susceptible to evolutionary changes than the first group ones. It is also discussed to use the W index as a biological stress value. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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17 pages, 11317 KiB  

Open AccessArticle

OxDNA to Study Species Interactions

by Francesco Mambretti, Nicolò Pedrani, Luca Casiraghi, Elvezia Maria Paraboschi, Tommaso Bellini and Samir Suweis

Entropy 2022, 24(4), 458; https://doi.org/10.3390/e24040458 - 26 Mar 2022

Cited by 3 | Viewed by 3241

Abstract

Molecular ecology uses molecular genetic data to answer traditional ecological questions in biogeography and biodiversity, among others. Several ecological principles, such as the niche hypothesis and the competitive exclusions, are based on the fact that species compete for resources. More in generally, [...] Read more.

Molecular ecology uses molecular genetic data to answer traditional ecological questions in biogeography and biodiversity, among others. Several ecological principles, such as the niche hypothesis and the competitive exclusions, are based on the fact that species compete for resources. More in generally, it is now recognized that species interactions play a crucial role in determining the coexistence and abundance of species. However, experimentally controllable platforms, which allow us to study and measure competitions among species, are rare and difficult to implement. In this work, we suggest exploiting a Molecular Dynamics coarse-grained model to study interactions among single strands of DNA, representing individuals of different species, which compete for binding to other oligomers considered as resources. In particular, the well-established knowledge of DNA–DNA interactions at the nanoscale allows us to test the hypothesis that the maximum consecutive overlap between pairs of oligomers measure the species’ competitive advantages. However, we suggest that a more complex structure also plays a role in the ability of the species to successfully bind to the target resource oligomer. We complement the simulations with experiments on populations of DNA strands which qualitatively confirm our hypotheses. These tools constitute a promising starting point for further developments concerning the study of controlled, DNA-based, artificial ecosystems. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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10 pages, 846 KiB  

Open AccessArticle

Tumor Hypoxia Heterogeneity Affects Radiotherapy: Inverse-Percolation Shell-Model Monte Carlo Simulations

by Argyris Dimou, Panos Argyrakis and Raoul Kopelman

Entropy 2022, 24(1), 86; https://doi.org/10.3390/e24010086 - 5 Jan 2022

Cited by 3 | Viewed by 2027

Abstract

Tumor hypoxia was discovered a century ago, and the interference of hypoxia with all radiotherapies is well known. Here, we demonstrate the potentially extreme effects of hypoxia heterogeneity on radiotherapy and combination radiochemotherapy. We observe that there is a decrease in hypoxia from [...] Read more.

Tumor hypoxia was discovered a century ago, and the interference of hypoxia with all radiotherapies is well known. Here, we demonstrate the potentially extreme effects of hypoxia heterogeneity on radiotherapy and combination radiochemotherapy. We observe that there is a decrease in hypoxia from tumor periphery to tumor center, due to oxygen diffusion, resulting in a gradient of radiative cell-kill probability, mathematically expressed as a probability gradient of occupied space removal. The radiotherapy-induced break-up of the tumor/TME network is modeled by the physics model of inverse percolation in a shell-like medium, using Monte Carlo simulations. The different shells now have different probabilities of space removal, spanning from higher probability in the periphery to lower probability in the center of the tumor. Mathematical results regarding the variability of the critical percolation concentration show an increase in the critical threshold with the applied increase in the probability of space removal. Such an observation will have an important medical implication: a much larger than expected radiation dose is needed for a tumor breakup enabling successful follow-up chemotherapy. Information on the TME’s hypoxia heterogeneity, as shown here with the numerical percolation model, may enable personalized precision radiation oncology therapy. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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19 pages, 4967 KiB  

Open AccessArticle

Breakdown of a Nonlinear Stochastic Nipah Virus Epidemic Models through Efficient Numerical Methods

by Ali Raza, Jan Awrejcewicz, Muhammad Rafiq and Muhammad Mohsin

Entropy 2021, 23(12), 1588; https://doi.org/10.3390/e23121588 - 27 Nov 2021

Cited by 22 | Viewed by 2935

Abstract

Background: Nipah virus (NiV) is a zoonotic virus (transmitted from animals to humans), which can also be transmitted through contaminated food or directly between people. According to a World Health Organization (WHO) report, the transmission of Nipah virus infection varies from animals to [...] Read more.

Background: Nipah virus (NiV) is a zoonotic virus (transmitted from animals to humans), which can also be transmitted through contaminated food or directly between people. According to a World Health Organization (WHO) report, the transmission of Nipah virus infection varies from animals to humans or humans to humans. The case fatality rate is estimated at 40% to 75%. The most infected regions include Cambodia, Ghana, Indonesia, Madagascar, the Philippines, and Thailand. The Nipah virus model is categorized into four parts: susceptible (S), exposed (E), infected (I), and recovered (R). Methods: The structural properties such as dynamical consistency, positivity, and boundedness are the considerable requirements of models in these fields. However, existing numerical methods like Euler–Maruyama and Stochastic Runge–Kutta fail to explain the main features of the biological problems. Results: The proposed stochastic non-standard finite difference (NSFD) employs standard and non-standard approaches in the numerical solution of the model, with positivity and boundedness as the characteristic determinants for efficiency and low-cost approximations. While the results from the existing standard stochastic methods converge conditionally or diverge in the long run, the solution by the stochastic NSFD method is stable and convergent over all time steps. Conclusions: The stochastic NSFD is an efficient, cost-effective method that accommodates all the desired feasible properties. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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16 pages, 4133 KiB  

Open AccessArticle

The Complementarity Principle—One More Step towards Analytical Docking on the Example of Dihydrofolate Reductase Complexes

by Vladimir Potemkin and Maria Grishina

Life 2021, 11(9), 983; https://doi.org/10.3390/life11090983 - 19 Sep 2021

Cited by 4 | Viewed by 2029

Abstract

New approaches to assessing the “enzyme–ligand” complementarity, taking into account hydrogens, have been proposed. The approaches are based on the calculation of three-dimensional maps of the electron density of the receptor–ligand complexes. The action of complementarity factors, first proposed in this article, has [...] Read more.

New approaches to assessing the “enzyme–ligand” complementarity, taking into account hydrogens, have been proposed. The approaches are based on the calculation of three-dimensional maps of the electron density of the receptor–ligand complexes. The action of complementarity factors, first proposed in this article, has been demonstrated on complexes of human dihydrofolate reductase (DHFR) with ligands. We found that high complementarity is ensured by the formation of the most effective intermolecular contacts, which are provided due to predominantly paired atomic–atomic interactions, while interactions of the bifurcate and more disoriented type are minimized. An analytical docking algorithm based on the proposed receptor–ligand complementarity factors is proposed. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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14 pages, 3441 KiB  

Open AccessArticle

Stochastic Analysis of Predator–Prey Models under Combined Gaussian and Poisson White Noise via Stochastic Averaging Method

by Wantao Jia, Yong Xu, Dongxi Li and Rongchun Hu

Entropy 2021, 23(9), 1208; https://doi.org/10.3390/e23091208 - 13 Sep 2021

Cited by 8 | Viewed by 2892

Abstract

In the present paper, the statistical responses of two-special prey–predator type ecosystem models excited by combined Gaussian and Poisson white noise are investigated by generalizing the stochastic averaging method. First, we unify the deterministic models for the two cases where preys are abundant [...] Read more.

In the present paper, the statistical responses of two-special prey–predator type ecosystem models excited by combined Gaussian and Poisson white noise are investigated by generalizing the stochastic averaging method. First, we unify the deterministic models for the two cases where preys are abundant and the predator population is large, respectively. Then, under some natural assumptions of small perturbations and system parameters, the stochastic models are introduced. The stochastic averaging method is generalized to compute the statistical responses described by stationary probability density functions (PDFs) and moments for population densities in the ecosystems using a perturbation technique. Based on these statistical responses, the effects of ecosystem parameters and the noise parameters on the stationary PDFs and moments are discussed. Additionally, we also calculate the Gaussian approximate solution to illustrate the effectiveness of the perturbation results. The results show that the larger the mean arrival rate, the smaller the difference between the perturbation solution and Gaussian approximation solution. In addition, direct Monte Carlo simulation is performed to validate the above results. Full article

(This article belongs to the Topic Stochastic Models and Experiments in Ecology and Biology)

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