Search arXivSearch

arXiv · 2401.14651

Nonlocal Models in Biology and Life Sciences: Sources, Developments, and Applications

Abstract

Nonlocality is important in realistic mathematical models of physical and biological systems when local models fail to capture the essential dynamics and interactions that occur over a range of distances. This review illustrates different nonlocal mathematical models applied to biology and life sciences. The major focus has been given to sources, developments, and applications of such models. Among other things, a systematic discussion has been provided for the conditions of pattern formations in biological systems of population dynamics. Special attention has also been given to nonlocal interactions on networks, network coupling and integration, including brain dynamics models that provide an important tool to understand neurodegenerative diseases better. In addition, we have discussed nonlocal modelling approaches for cancer stem cells and tumor cells that are widely applied in the cell migration processes, growth, and avascular tumors in any organ. Furthermore, the discussed nonlocal continuum models can go sufficiently smaller scales, including nanotechnology, where classical local models often fail to capture the complexities of nanoscale interactions, applied to build biosensors to sense biomaterial and its concentration. Piezoelectric and other smart materials are among them, and these devices are becoming increasingly important in the digital and physical world that is intrinsically interconnected with biological systems. Additionally, we have reviewed a nonlocal theory of peridynamics, which deals with continuous and discrete media and applies to model the relationship between fracture and healing in cortical bone, tissue growth and shrinkage, and other areas increasingly important in biomedical and bioengineering applications. Finally, we provided a comprehensive summary of emerging trends and highlighted future directions in this rapidly expanding field.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Swadesh Pal, Roderick Melnik. 2025-02-13. Nonlocal Models in Biology and Life Sciences: Sources, Developments, and Applications. https://arxiv.org/abs/2401.14651

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Lightning-fast adaptive immune receptor similarity search by symmetric deletion lookup

An individual's adaptive immune receptor (AIR) repertoire records immune history due to the receptors' antigen specificity. Reading this record requires computational approaches for inferring receptor function from sequence, as the diversity of possible receptor-antigen pairs vastly outstrips experimental knowledge. Identification of AIRs with similar sequence and thus putatively similar function is a common performance bottleneck in these approaches. Here, we benchmark the runtime scaling of five algorithmic approaches to radius-based search for Levenshtein neighbors. We show that a symmetric deletion lookup approach, originally proposed for spell-checking, is particularly scalable. We introduce SymScan and XTNeighbor, optimized CPU and GPU software implementing a parallelized variant of the algorithm. For one million input sequences, these tools identify all sequence pairs that differ by one or two edits in seconds, orders of magnitude faster than existing approaches. We demonstrate how symmetric deletion lookup can be integrated as a pre-filtering step in T cell receptor metaclone discovery and B cell receptor lineage identification. Our contribution is poised to greatly accelerate existing analysis pipelines and enable processing of immunosequencing data at scale.

q-bio.QM

Implication of modelling choices on connectivity estimation: A comparative analysis

Landscape connectivity is an important field with important conservation implications. Connectivity modelling is a useful tool to inform and guide landscape planning. However, it involves assumptions and methodological decisions which ultimately impact connectivity outcomes. In order to understand the implications of modelling choices on final connectivity estimations, we compare two landscape characterisation approaches - expert knowledge and species distribution models - and three movements models - least-cost paths, circuit theory and an individual-based movement simulator. The implementation of the models and the construction of the analyses scope highlighted conceptual and methodological differences that made the comparison difficult. Landscape characterisation appears as the principal factor determining connectivity outcomes. Therefore, the confrontation between expert knowledge and species distribution models is critical to leverage points of convergence and complementarity between these two approaches. Conceptual differences between movement models are reported on connectivity map and habitat patch contribution estimations. In the want of data and protocol design specifically to validate connectivity models, approaches that integrate stochastic and behavioural processes, bring a more realistic perspective to connectivity estimation.

q-bio.QM

Triplication: an important component of the modern scientific method

A scientific-study protocol (defined) is designed to deliver results from which inductive inference is allowed. In the nineteenth century, triplication was introduced into the plant sciences and Fisher's p<0.05 rule (1925) incorporated into triple-result protocols designed to counter random/systematic errors which contribute to real-world variability. The aims of the present study were to: (1) classify replication protocols; (2) assess their prevalence in plant-science studies (published during one twenty-first-century year; for defined variable construct); (3) explore triplication rationale. Methods: a plant-sciences protocol-prevalence report was produced; experimental/associational-study proportions analyzed; and real-world-data proxies used to show confidence-interval-width patterns with increasing replicate number. Results: 25% plant-science studies analyzed showed triplication, including 11% triple-result protocols (including greater replicate numbers: 48%;17%, respectively). Theoretical considerations indicated that even if systematic errors predominate, (previously-known) square-root rules sometimes apply, contributing to triplication importance (exemplified by real-world-data proxies). Conclusions: The defined protocols, with minor modifications, should provide the means for assessment of most sciences. Triplication was extensively applied in studies analysed and there are strong methodological reasons why triplication, rather than duplication/quadruplication, is the appropriate standard: triple-result protocols: (a) effectively reduce false positives to acceptable levels; (b) give qualitatively-different information (shape) from duplication; (c) have a large efficiency advantage (concerning confidence-interval widths) over quadruplication. The application of batch replication is not, primarily, a statistical problem and cannot effectively be replaced by simulation.

q-bio.QM