As of June 2026, more than 18.5 million SARS-CoV-2 genomes have been collected and sequenced worldwide, creating a viral dataset of unprecedented scale. Such collections provide exceptional opportunities for studying viral evolution, including the dynamics of nucleotide substitutions, deletions, insertions, recombination-related patterns, and the emergence and spread of new variants across geographic regions. Although several web resources provide access to genome repositories and online analytical tools, many research problems still require local computation with custom algorithms, user-defined workflows, and private or unpublished sequences. In these settings, computational efficiency depends critically on how genomic data are loaded, represented, stored, and processed. Here we present ScateClave, an open-source software complex for local analysis and tracking of evolutionary changes in large viral genome collections. The system was developed and practically validated on SARS-CoV-2. Its computational core is implemented in C++, whereas static and interactive visualization is provided in Python. ScateClave is designed for efficient loading, sparse in-memory representation, and scalable downstream analysis of annotated genomes on a single workstation. The complex produces several coordinated analytical outputs, including a time-distance landscape, position-specific change matrices across the coding region, sliding-window profiles for Pango lineages, graphs of locally plausible transitions, and reconstructed paths between genome states. Although the current implementation and validation are specific to SARS-CoV-2, the underlying algorithms rely on general operations over sparse genomic events, temporal indices, and metadata, making the approach extensible to other viruses and suitable as a foundation for developing new large-scale genomic analysis methods.
Understanding the mechanisms that determine population dynamics and structure is essential for assessing the long-term persistence of species and communities under changing environmental conditions, as well as for developing optimal strategies for natural resource management. This paper proposes a population model consisting of four age–sex groups. An additional equation describes a situation typical of harvested species (e.g., pinnipeds and ungulates): males that have reached sexual maturity do not breed for several seasons because they cannot compete for females with older, larger reproductive males. Introducing this group allows, first, a more detailed description of the life cycle – specifically, accounting for reduced survival upon entering the reproductive stage due to competitive struggle for harems. Second, this model is convenient for studying selective harvesting, where non-breeding individuals are removed – a practice often used to preserve the reproductive potential of a population. We perform an analytical and numerical study of the proposed four-component model with seasonal breeding and birth rate dependent on the sex ratio. Additionally, we analyze the influence of within‑population parameters on the average harem size and its productivity. We show that the loss of stability of the nontrivial equilibrium in the biologically meaningful parameter range occurs only via a Neimark–Sacker bifurcation, leading to quasiperiodic oscillations. Fluctuations in population size arise at high values of the birth rate coefficient, which is typical for species with multiple offspring per pregnancy (e.g., wild boar). In species with single offspring per pregnancy and one breeding season per year (e.g., northern fur seal and most pinnipeds), the birth rate coefficient does not exceed unity; therefore, the nontrivial equilibrium is stable, and observed population fluctuations may be attributed to external factors – changes in environmental conditions, food availability, or harvesting.
Investigations focused on how malignant tumors appear and grow in the body are complicated due to multi-level regulation, which makes direct experimental in vivo studies rather difficult. A mathematical model presented in this study describes dynamics of changes in the quantity of abnormal cells taking angiogenesis processes and immune system reactions into account. The model has been developed within a multi-level approach, which considers interactions between the systems in the body and functional state of various organs. Time lags, which reflect interactions between various components of the system, have been introduced in the model in order to describe spatial organization of oncological processes in various tissues. The suggested approach is based on a prediction model, which considers dynamics of changes in the number of abnormal cells, regulatory pathways and angiogenesis processes. The Monte-Carlo method is employed to analyze possible tumor growth scenarios. The results obtained by numeric experiments reflect both quantitative (growth/decline in cell numbers) and spatial (tumor localization, vessel distribution) changes. We have analyzed impacts exerted on tumor growth by the immune system parameters and characteristics of abnormal cells. Cell division rates, the immune system activity and angiogenesis dynamics are key factors in the process. The suggested model makes it possible to assess the role that belongs to biological factors in tumor growth kinetics and provides necessary data for qualitative understanding of pathways, which determine malignant neoplasm progression. Our findings can be used for further investigations on the role of angiogenesis and immune regulation in tumor growth.
The article discusses the effect of substituting calcium ions Ca 2+ in certain positions of hydroxyapatite with iron ions Fe 2+ and Fe 3+ . It shows how to use molecular dynamics simulations with a skewed cell in periodic boundary conditions to find the density of hydroxyapatite. The obtained density values are in good agreement with known data and the results of density functional theory calculations. The article also describes the process of ion evaporation, melting, and sublimation of different hydroxyapatite samples. The molecular dynamics simulation results show significant differences in the temperatures of structural rearrangements for hydroxyapatite with Fe 2+ and Fe 3+ substitutions. For example, the hydroxyapatite sample with Fe 2+ ions experiences significant structural rearrangements in the temperature range of 727–827 °C, which is consistent with the experimental data on the decomposition of cation-substituted hydroxyapatite with iron ions at temperatures around 800 °C.
In the work presented, we study the nature of motion and distribution of charge along a chain during its Bloch oscillations in a constant electric field. Previous calculations have shown that the nature of the charge motion and distribution along the chain depends on the entire set of system parameters. For example, if only the intensity of an electric field or the initial charge distribution is changed, there may be either uniform motion or oscillatory motion when all other parameters of the system remain unchanged. In this work, the modeling of charge dynamics in a constant electric field was carried out in polynucleotide chains with different parameters of the oscillation frequency of chain sites and the friction coefficient. The conducted researches showed significant differences in the velocity and nature of charge motion in chains with different values of the specified parameters. Obviously, the study of charge motion in polynucleotide chains, whose parameters are close to those of DNA chains, is of the greatest interest. But numerical modeling of the charge dynamics in such chains tends to be more costly for computational resources. Therefore, in order to speed up the computations carried out, modelling is first performed in chains with more convenient parameters. It has been shown that in chains with parameters close to those of DNA chains, the charge can only move slightly along the chain, oscillating in the region of its initial position. With model values of the oscillation frequency of the chain sites and the friction coefficient, which significantly exceed the corresponding values of the parameters of DNA chains, the charge can move along the chain over a sufficiently large distance.
