22 papers · ranked by Valyu relevance
Neveen Ali Eshtewy, Ali Forootani, Zahra Ahangari Sisi
Mathematical modeling has become an indispensable tool for understanding, predicting, and controlling the spread of infectious diseases. Over the years, a wide variety of models have been developed to analyze disease dynamics and forecast epidemic trajectories. Deterministic and stochastic frameworks provide…
Marzieh Asgari-Targhi, Amene Asgari-Targhi, Mahboubeh Asgari-Targhi, Edward J. + 1 more
Over the past two decades, the rapid surge in data-intensive computational techniques for statistical modeling may have had the effect of diminishing the use of applied mathematics in causal scientific inquiry. In this paper, co-authored by an astrophysicist, a mathematician, and philosophers, we assess the hazards of…
Nejla Gürefe, Hava Öksüz, Gülfem Sarpkaya Aktaş, Annesha Sil
In the 21st century, advancements in technology have significantly transformed the educational landscape, prompting innovations in mathematics curricula .Accordingly, mathematics education aims to link mathematics with daily life and to enable students to mathematically interpret and analyse the events they encounter…
Jamie A. Lopez, Amir Erez
Mathematical models are increasingly a part of microbiological research. Here, we share our perspective on how modeling advances the discipline by: (i) enforcing logical consistency, (ii) enabling quantitative prediction, (iii) extracting hidden parameters from data, and (iv) generating intuitive understanding. We map…
Penelope A. Morel, Jaroslaw Smieja, Urszula Foryś
Mathematical modeling is an important tool that facilitates formulation and initial testing of hypotheses concerning properties of biological systems, mechanisms controlling their behavior, and novel therapy protocols as well as support analysis of the increasingly large and complex datasets containing experimental and…
S.A. Lashin, R.A. Ivanov, Y.G. Matushkin
of biosystems at different levels of organization Математическое и компьютерное моделирование биологических систем на разных иерархических уровнях организации Authors: S.A. Lashin, R.A. Ivanov, Y.G. Matushkin Modern biology increasingly relies on mathematical and computational modeling to describe complex…
Franco Pradelli, Maximilian Strobl, Sadegh Marzban, François de Kermenguy + 8 more
Constructing a comprehensive overview of any scientific field requires accurate literature selection, yet conventional keyword-based searches are susceptible to false positives. This problem is magnified in growing or interdisciplinary fields such as mathematical modeling in oncology that contain a rich but…
Maggie McCarter, Stella C W Self, Alex Ewing, Mufaro Kanyangarara + 3 more
Statistical modeling of infectious disease transmission patterns has been in existence since the mid-1700s, evolving in their utility as the scientific and technological revolutions progressed. Despite the expansion of emerging mathematical and statistical methodologies over the past 250 yr, their usage has largely…
Andrea Polo-Rodríguez, David R. Penas, Julio R. Banga
Parameter estimation is a central challenge in systems biology, particularly for large dynamic models described by nonlinear ordinary differential equations (ODEs). These global optimization problems exhibit landscapes which are topologically heterogeneous, often exhibiting a pathological mixture of stiff, smooth…
Marco Polo Castillo-Villalba
The analysis of large gene and metabolic networks is often hindered by unknown biochemical parameters and the nonlinear nature of classical S-system models. To address this, we introduce a framework based on combinatorial toric geometry computed with tools such as Normaliz, SageMath, it is worth mentioning this…
Tsubasa Sukekawa, Toshiaki Yachimura, Sungrim Seirin-Lee
The geometrical properties of a cell are not merely passive consequences of cellular function but actively regulate key biological processes during development, morphogenesis, and disease. Although modern live-imaging techniques now allow detailed monitoring of cell morphology, incorporating such complex geometrical…
Niklas Neubrand, Timo Rachel, Tim Litwin, Jens Timmer + 2 more
Systems biology strives to unravel the complex dynamics of cellular processes, often with the help of ordinary differential equations (ODEs). However, the sparsity of measured data and the strong non-linearity of common ODEs introduce severe numerical problems in typical modeling tasks. This gave rise to the…
Leeroy Makusha, Preston Abadie, Donald J. Docimo
Design, control, and estimation for dynamic systems require accurate and analytically tractable models. However, modern engineered systems contain components that are described with heterogeneous modeling paradigms, as well as subsystems that are challenging to model from physics alone. There have been significant…
Mustaq Ahmad, Archana Singh Bhadauria
This study develops a compartmental epidemic model for Hepatitis B virus (HBV) transmission incorporating vertical transmission, spontaneous recovery in acutely infected individuals, saturated treatment response for chronically infected individuals, and vaccination of susceptible individuals. The basic reproduction…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Abadi Abraha Asgedom, Yohannes Yirga Kefela
Cancer remains a global health challenge requiring sophisticated understanding of tumor-immune dynamics for effective treatment design. Mathematical oncology has emerged as a rapidly evolving interdisciplinary field that uses mathematical models to enhance our understanding of cancer dynamics, including tumor growth…
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Developing a transferable classical force field (FF) has historically been a lengthy, expert-informed process. In this work, we integrate optimization, machine learning, and data science techniques to accelerate the systematic design and parameterization of transferable FF models. As a demonstration, we create…
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This conceptual paper introduces the Adaptive Multi-Resolution Modeling Framework (AMRMF), a novel technique designed to revolutionize chemical engineering by integrating multi-scale simulations, quantum-inspired algorithms, advanced uncertainty quantification, and Bayesian inference. The framework bridges theoretical…
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Accurate modeling of drug concentration--time (C--t) profiles is central to pharmacokinetics (PK) and plays a critical role in both early-stage compound selection and late-stage individualized dosing. Traditional PK model offer mechanistic interpretability but often rely on rigid assumptions, extensive…
Jonas Pleyer
Cellular Agent-Based Models are commonly employed to describe a variety biological systems. Over the course of the past years, many modeling tools have emerged which solve particular research questions. In this short opinion piece, we argue that existing frameworks lack flexibility compared to the inherent underlying…
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The rigorous design of adsorption-based separation processes, such as Pressure Swing Adsorption (PSA) and Temperature Swing Adsorption (TSA), is fundamentally dependent on the accuracy of the underlying mathematical models describing equilibrium isotherms and transport kinetics. However, the current state of the art is…
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The integration of machine learning methods is transforming many areas of research by, for instance, accelerating molecular dynamics simulations and enabling improved prediction and optimization of chemical reactions. However, despite this progress, the adoption of data-driven approaches in atomic layer deposition…