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Quantitative Modelling in Stem Cell Biology and Beyond: How to Make Best Use of It

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CURRENT STEM CELL REPORTS
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SPRINGER HEIDELBERG
DOI: 10.1007/s40778-023-00230-7

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Quantitative modelling; Advanced hypothesis testing; Universality; Over-fitting

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This article gives an overview of quantitative modelling approaches in biology and provides guidance on how to use them in stem cell research. It points out that while quantitative modelling can boost biological research, careful considerations need to be taken to avoid pitfalls and understand its limitations.
Purpose of ReviewThis 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 FindingsThe twenty-first century has seen a steady increase in the proportion of cell biology publications employing mathematical modelling to aid experimental research. However, quantitative modelling is often used as a rather decorative element to confirm experimental findings, an approach which often yields only marginal added value, and is in many cases scientifically questionable.SummaryQuantitative modelling can boost biological research in manifold ways, but one has to take some careful considerations before embarking on a modelling campaign, in order to maximise its added value, to avoid pitfalls that may lead to wrong results, and to be aware of its fundamental limitations, imposed by the risks of over-fitting and universality.

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