Fitting structure to function in gene regulatory networks

The idea of constancy in development and evolution - Scientific and philosophical perspectives

The ability of developmental systems to produce constant phenotypes, even in a wide range of different environments, and the longstanding stability of species are among the most remarkable phenomena in biology. I argue that understanding the longstanding constancy and stability of species or the constant outcome of development in different environments are also prerequisites for explaining stable change (i.e., change that does not consist of random plasticity). Various approaches to account for stable changes in development are based on the causal role of genes and an organized genome, mathematical-physical-chemical models, or a combination of both. I argue that the constancy of developmental outcome and the longstanding stability of species are associated with organisms' structural and organizational hierarchies, particularly highly organized gene-regulatory networks and genetic causality, which are fundamental principles of life. Mathematical-physical-chemical models that marginalize these principles cannot convincingly account for the observed constancy in development and evolution. However, an integration of physical-chemical processes such as reaction-diffusion mechanisms and genome-based mechanisms of form generation has recently proved fruitful in explaining the development of some periodic structures. Constancy and change were also major topoi in ancient Greek philosophy, in which prominent philosophical schools such as the atomists attempted to bridge the antinomy between them by basing stable change on constant entities. I argue that the idea of change, that is, change without losing complexity or even increasing it, being based on modifications of the otherwise reliable transmission of genomes over long periods of time has a historical parallel in the writings of these ancient speculative thinkers, notwithstanding the fundamental differences between the two thought systems.

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

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 hypothetico-deductive, 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.

Mechanistic philosophies of development: Theodor Boveri and Eric H. Davidson

Theodor Boveri's (1862-1915) and Eric Davidson's (1937-2015) achievements represent thoroughly two quite distant time frames in the history of the mechanistic approaches to development, that Jane Maienschein (2014) has characterized respectively as the era of the "experimental embryo" and of the "computed embryo". Nonetheless, Davidson's special bond to Boveri is meant to emphasize the genealogical continuity of an embryological tradition of mechanistic philosophy that, differently from molecular biology, is committed to an explanation of the hereditary transmission of organization. Davidson's genealogical claim is reconsidered through a contextualized analysis of the function of machine-like models and of the role of experiment in the making of their respective mechanistic philosophies. This analysis may help to shed light on resilience and change in the understanding of a mechanistic approach to development.