27 papers · ranked by Valyu relevance
Hans-Stefan Siller, Hans-Jürgen Elschenbroich, Gilbert Greefrath, Katrin Vorhölter
'Katrin Vorhölter'] Mathematical concepts are regularly used in media reports concerning the Covid-19 pandemic. These include growth models, which attempt to explain or predict the effectiveness of interventions and developments, as well as the reproductive factor. Our contribution has the aim of showing that basic…
Sergej Pankratow
| Summary 8 | | |--------------------------------------------------------------------|----| | 1. Introduction8 | | | Section 2. Basic types of mathematical models14 | | | Section 3. Expected properties of mathematical and computer models | 20 | | 3.1. Theory, experiment and models26 | | | 3.2. The economy principle30 |…
Nestor V. Torres, Guido Santos
In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the…
Aaditya Prasad Gupta
A modeling is a mathematical tool, like a microscope, which allows consequences to logically follow from a set of assumptions by which a real world problem can be described by a mathematical formulation. It has become indispensable tools for integrating and interpreting heterogeneous biological data, validating…
Authors not listed
Within the biological, physical, and social sciences, there are two broad quantitative traditions: statistical and mathematical modeling. Both traditions have the common pursuit of advancing our scientific knowledge, but these traditions have developed largely independently using distinct languages and inferential…
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…
Vitaly V. Ganusov
While there are many opinions on what mathematical modeling in biology is, in essence, modeling is a mathematical tool, like a microscope, which allows consequences to logically follow from a set of assumptions. Only when this tool is applied appropriately, as microscope is used to look at small items, it may allow to…
Teegwendé V. Porgo, Susan L. Norris, Georgia Salanti, Leigh F. Johnson + 4 more
'Leigh F. Johnson' 'Julie A. Simpson' 'Nicola Low' 'Matthias Egger' 'Christian L. Althaus'] Mathematical modeling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision-making, particularly when data from systematic reviews of primary studies do…
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…
Marvin van Aalst, Oliver Ebenhöh, Anna Matuszyńska
Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies and disease evolution or transmission. Unfortunately, despite community efforts leading to the development of…
Julio Vera, Christopher Lischer, Momchil Nenov, Svetoslav Nikolov + 2 more
'Xin Lai' 'Martin Eberhardt'] In most disciplines of natural sciences and engineering, mathematical and computational modelling are mainstay methods which are usefulness beyond doubt. These disciplines would not have reached today’s level of sophistication without an intensive use of mathematical and computational…
Patrik Christen, Olivier Del Fabbro
Mathematical modelling heavily employs differential equations to describe the macroscopic or global behaviour of systems. The dynamics of complex systems is in contrast more efficiently described by local rules and thus in an algorithmic and local or microscopic manner. The theory of such an approach has to be…
Philip Greulich
Purpose of Review This article gives a broad overview of quantitative modelling approaches in biology and provides guidance on how to employ them to boost stem cell research, by helping to answer biological questions and to predict the outcome of biological processes. Recent Findings The twenty-first century has seen a…
David J. Warne, Ruth E. Baker, Matthew J. Simpson
Reaction–diffusion models describing the movement, reproduction and death of individuals within a population are key mathematical modelling tools with widespread applications in mathematical biology. A diverse range of such continuum models have been applied in various biological contexts by choosing different flux and…
Pietro Gerletti, Nils Gubela, Jean-Baptiste Escudié, Denise Kühnert + 1 more
Computational tools are frequently used to describe pathogen evolutionary dynamics either within infected hosts or at the population level. However, there is a lack of models that capture the complex interplay between within-host and between-host evolutionary dynamics, leaving a knowledge gap with regard to realistic…
Ramón Nartallo-Kaluarachchi, Renaud Lambiotte, Alain Goriely
—At its core, the physics paradigm adopts a reductionist approach to modelling, aiming to understand fundamental phenomena by decomposing them into simpler, elementary processes. While this strategy has been tremendously successful in physics and is typically considered the pinnacle of scientific formulation, it has…
Ron Henkel, Robert Hoehndorf, Tim Kacprowski, Christian Knüpfer + 2 more
Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational…
Sean T. Vittadello, Michael P. H. Stumpf
Biology is data-rich, and it is equally rich in concepts and hypotheses. Part of trying to understand biological processes and systems is therefore to confront our ideas and hypotheses with data using statistical methods to determine the extent to which our hypotheses agree with reality. But doing so in a systematic…
Michael P.H. Stumpf
The development of mathematical models of biological systems has largely relied on a mix of biological intuition, mathematical expediency, and comparisons with data. Models are hard to develop and hard to validate. Recent progress in theoretical systems biology, applied mathematics and computational statistics has…
Carley V. Cook, Ariel M. Lighty, Brenda J. Smith, Ashlee N. Ford Versypt
Bone remodeling is an essential physiological process in the adult skeleton. Due to the complex nature of this process, many mathematical models of bone remodeling have been developed. Each of these models has unique features, but they have underlying patterns. In this review, the authors highlight the important…
Yasmin Z. Paterson, David Shorthouse, Markus W. Pleijzier, Nir Piterman + 3 more
In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of…
Andrea Saltelli
Statistics experiences a storm around the perceived misuse and possible abuse of its methods in the context of the so-called reproducibility crisis. The methods and styles of quantification practiced in mathematical modelling rarely make it to the headlines, though modelling practitioners writing in disciplinary…
Anna Matuszyńska, Oliver Ebenhöh, Matias D. Zurbriggen, Daniel C. Ducat + 1 more
Synthetic biology designs and constructs new biological parts, devices and systems with predetermined functionalities. With the unlimited ability to synthesise any DNA and RNA and transfer it to almost any organism, we are at the dawn of a new era in which biology is being recreated in ways never before possible. It…
Muhammad Farman, Muhammad Farhan Tabassum, Muhammad Saeed, Nazir Ahmad Chaudhry
Hepatitis B is the main public health problem of the whole world. In epidemiology, mathematical models perform a key role in understanding the dynamics of infectious diseases. This paper proposes Padé approximation (Pa) with Differential Evolution (DE) for obtaining solution of Hepatitis-B model which is nonlinear…
Authors not listed
The use of hybrid models, combing mechanistic and machine learning (ML), has emerged as a promising approach, contributing to the development of Industry 4.0. This work presents a hybrid model that forecasts minibioreactor (MBR) production runs of mammalian cell culture recombinant for monoclonal antibodies (mAbs)…
Liwei Cao, Danilo Russo, Vassilios S. Vassiliadis, Alexei Lapkin
A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor…
Authors not listed
This paper presents the Multi Cell-line Kinetic Model (MCKM), a novel generalised kinetic mechanistic model specifically tailored for Ambr15™ fed-batch cultivations of multiple Chinese Hamster Ovary (CHO) cell lines producing different recombinant monoclonal antibodies (mAbs). Unlike traditional models that requires…