Bringing the physical sciences into your cell biology research

Robinson, Douglas N.; Iglesias, Pablo A.

doi:10.1091/mbc.e12-05-0354

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Over the last 20 years, the presence of these interdisciplinary teams has grown tremendously, but there is room for more. Previously we argued that a critical step to a successful interdisciplinary collaboration is a commitment to learn each other's scientific languages (Robinson & Iglesias, 2012). This is still true today.…”

Section: Discussion and Outlookmentioning

confidence: 99%

Tools for computational analysis of moving boundary problems in cellular mechanobiology

DiNapoli¹,

Robinson²,

Iglesias

2020

WIREs Mechanisms of Disease

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A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non‐expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health.This article is categorized under: Cancer > Computational Models Cancer > Molecular and Cellular Physiology

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Section: Discussion and Outlookmentioning

confidence: 99%

Tools for computational analysis of moving boundary problems in cellular mechanobiology

DiNapoli¹,

Robinson²,

Iglesias

2020

WIREs Mechanisms of Disease

Self Cite

View full text Add to dashboard Cite

show abstract

Applying Beer’s Law in the undergraduate cell biology laboratory: examining the mathematical relationship between optical density, cell concentration, and cell size using budding yeast

Brito,

Rohan,

Buffum-Robbins

et al. 2024

J Microbiol Biol Educ.

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Undergraduate students majoring in the life sciences benefit from experience with data analyses that connect mathematical calculations to the biological systems they are studying. Monitoring the optical density and cell number of Saccharomyces cerevisiae liquid cultures allows students to gain quantitative experience generating standard curves and trendlines that capture the relationship between optical density and cell concentration for a given S. cerevisiae strain. Data comparisons across multiple strains can yield insights into the biophysical properties of cells that drive light absorbance and scattering. In this Tips and Tools article, we share a laboratory module that allows students to experience cell biology tools, laboratory measurements, and data analysis to determine the mathematical relationship between optical density and cell concentration in liquid microbial cultures. This module could be integrated into undergraduate classes ranging from general biology to upper-level cell biology or microbiology and can be a starting point for more complex investigations of microbial growth.

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Bringing the physical sciences into your cell biology research

Cited by 2 publications

References 19 publications

Tools for computational analysis of moving boundary problems in cellular mechanobiology

Tools for computational analysis of moving boundary problems in cellular mechanobiology

Applying Beer’s Law in the undergraduate cell biology laboratory: examining the mathematical relationship between optical density, cell concentration, and cell size using budding yeast

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