Literature DB >> 25280665

The role of mathematical models in understanding pattern formation in developmental biology.

David M Umulis1, Hans G Othmer.   

Abstract

In a Wall Street Journal article published on April 5, 2013, E. O. Wilson attempted to make the case that biologists do not really need to learn any mathematics-whenever they run into difficulty with numerical issues, they can find a technician (aka mathematician) to help them out of their difficulty. He formalizes this in Wilsons Principle No. 1: "It is far easier for scientists to acquire needed collaboration from mathematicians and statisticians than it is for mathematicians and statisticians to find scientists able to make use of their equations." This reflects a complete misunderstanding of the role of mathematics in all sciences throughout history. To Wilson, mathematics is mere number crunching, but as Galileo said long ago, "The laws of Nature are written in the language of mathematics[Formula: see text] the symbols are triangles, circles and other geometrical figures, without whose help it is impossible to comprehend a single word." Mathematics has moved beyond the geometry-based model of Galileo's time, and in a rebuttal to Wilson, E. Frenkel has pointed out the role of mathematics in synthesizing the general principles in science (Both point and counter-point are available in Wilson and Frenkel in Notices Am Math Soc 60(7):837-838, 2013). We will take this a step further and show how mathematics has been used to make new and experimentally verified discoveries in developmental biology and how mathematics is essential for understanding a problem that has puzzled experimentalists for decades-that of how organisms can scale in size. Mathematical analysis alone cannot "solve" these problems since the validation lies at the molecular level, but conversely, a growing number of questions in biology cannot be solved without mathematical analysis and modeling. Herein, we discuss a few examples of the productive intercourse between mathematics and biology.

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Year:  2014        PMID: 25280665      PMCID: PMC4819020          DOI: 10.1007/s11538-014-0019-7

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  62 in total

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Authors:  Jason N Bazil; Gregory T Buzzard; Ann E Rundell
Journal:  Bull Math Biol       Date:  2011-10-12       Impact factor: 1.758

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Journal:  Interface Focus       Date:  2012-03-21       Impact factor: 3.906

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Journal:  Bioessays       Date:  2007-06       Impact factor: 4.345

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7.  Exploring the effects of mechanical feedback on epithelial topology.

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8.  The bicoid protein determines position in the Drosophila embryo in a concentration-dependent manner.

Authors:  W Driever; C Nüsslein-Volhard
Journal:  Cell       Date:  1988-07-01       Impact factor: 41.582

9.  Organism-scale modeling of early Drosophila patterning via bone morphogenetic proteins.

Authors:  David M Umulis; Osamu Shimmi; Michael B O'Connor; Hans G Othmer
Journal:  Dev Cell       Date:  2010-02-16       Impact factor: 12.270

10.  The decapentaplegic gene is required for dorsal-ventral patterning of the Drosophila embryo.

Authors:  V F Irish; W M Gelbart
Journal:  Genes Dev       Date:  1987-10       Impact factor: 11.361

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  9 in total

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Journal:  J Math Biol       Date:  2020-01       Impact factor: 2.259

3.  Improving Parameter Inference from FRAP Data: an Analysis Motivated by Pattern Formation in the Drosophila Wing Disc.

Authors:  Lin Lin; Hans G Othmer
Journal:  Bull Math Biol       Date:  2017-01-18       Impact factor: 1.758

4.  Acceleration of PDE-Based Biological Simulation Through the Development of Neural Network Metamodels.

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5.  Evaluation of BMP-mediated patterning in a 3D mathematical model of the zebrafish blastula embryo.

Authors:  Linlin Li; Xu Wang; Mary C Mullins; David M Umulis
Journal:  J Math Biol       Date:  2019-11-26       Impact factor: 2.164

6.  Self-organization of network dynamics into local quantized states.

Authors:  Christos Nicolaides; Ruben Juanes; Luis Cueto-Felgueroso
Journal:  Sci Rep       Date:  2016-02-17       Impact factor: 4.379

7.  Pattern Formation through Temporal Fractional Derivatives.

Authors:  Hongwei Yin; Xiaoqing Wen
Journal:  Sci Rep       Date:  2018-03-22       Impact factor: 4.379

Review 8.  Of mitogens and morphogens: modelling Sonic Hedgehog mechanisms in vertebrate development.

Authors:  Ian Groves; Marysia Placzek; Alexander G Fletcher
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-08-24       Impact factor: 6.237

9.  Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation.

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Journal:  Entropy (Basel)       Date:  2022-01-10       Impact factor: 2.524

  9 in total

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