From Gregor Mendel to Eric Davidson: Mathematical Models and Basic Principles in Biology

Journal of computational biology

article

DeichmannUte¹ 

[1] Jacques Loeb Centre for the History and Philosophy of the Life Sciences Ben-Gurion University of the Negev Beersheba 8410501 Israel

关键词: gene regulatory networks;    Eric Davidson;    Alan Turing;    D’Arcy Thompson;    genetic causality;    biological specificity.;   

DOI  :  10.1089/cmb.2019.0087

来源: Mary Ann Liebert, Inc. Publishers

【 摘 要 】

Mathematical models have been widespread in biology since its emergence as a modern experimental science in the 19th century. Focusing on models in developmental biology and heredity, this article (1) presents the properties and epistemological basis of pertinent mathematical models in biology from Mendel’s model of heredity in the 19th century to Eric Davidson’s model of developmental gene regulatory networks in the 21st; (2) shows that the models differ not only in their epistemologies but also in regard to explicitly or implicitly taking into account basic biological principles, in particular those of biological specificity (that became, in part, replaced by genetic information) and genetic causality. The article claims that models disregarding these principles did not impact the direction of biological research in a lasting way, although some of them, such as D’Arcy Thompson’s models of biological form, were widely read and admired and others, such as Turing’s models of development, stimulated research in other fields. Moreover, it suggests that successful models were not purely mathematical descriptions or simulations of biological phenomena but were based on inductive, as well as hypotheticodeductive, methodology. The recent availability of large amounts of sequencing data and new computational methodology tremendously facilitates system approaches and pattern recognition in many fields of research. Although these new technologies have given rise to claims that correlation is replacing experimentation and causal analysis, the article argues that the inductive and hypothetico-deductive experimental methodologies have remained fundamentally important as long as causal-mechanistic explanations of complex systems are pursued.

【 授权许可】

Unknown