The Changing Beauty of Biology

Biologists are usually afraid of mathematics. For a long time, the best they were at attempting a biological phenomenon mathematically were the second order differential equations regarding enzyme kinetics. Development, which is the most unclear of concepts in biology might benefit from mathematical characterization. I am currently studying a book, titled Modularity in development and evolution, on viewing genetic and development networks as modules which are repeatedly used across space and time.

Here are two beautiful excerpts from the beginning of one of the chapters in the book. The first describes how systems approach might go a long way in solving the puzzles of development.

“If one is seeking a biochemical understanding of development then the language of dynamical systems theory seems a natural one to use.
If we are serious about attempting to understand the hierarchy of developmental decisions in molecular terms then we do not just need to identify the molecular terms then we do not just need to identify the relevant genes and gene products but also to understand their dynamical behaviour. In the past this has proved to be necessary for understanding such things as the mechanism of nerve conduction or aggregation in slime moulds. In the future it seems probable that it will be through the mathematics of dynamical systems theory that embryological and molecular results can meaningfully be brought together.”
J. M. W. Slack, From Egg to Embryo

Here is another excerpt which reflects on the changing nature of biological research and being inspired from Nature, something which I have written about earlier.

“1980 in some ways marked the end of the Age of Beautiful Theories in biology, and the dawn of the Age of Ugly Facts. . . . If double-helical model of the structure of DNA showed that imagination (with a sprinkling of data) could triumph over Nature, Nüsslein-Volhard and Wieschaus’s saturation mutaagenesis showed that evolution can produce biological mechanisms of such unimaginable complexity that it would be useless, if not laughable, to try to intuit them a priori. Nature’s imagination, it showed, usually far outstrips the human brain. . . the baroque and counter-intuitive biological mechanisms that evolution has produced so often mock the human imagination.”
Anderson and Walter, 1999

Viewing biological systems as replicate modules within modules would allow us to design better ones: one of the objectives of synthetic biology. Synthetic biology leverages on the advancements in cell, molecular and systems biology. Add a pinch of mathematical rigour and the future is scripted.


2 thoughts on “The Changing Beauty of Biology

  1. Until recently I would argue that there hasn’t been enough molecular data to start mathematically modelling development to any degree of accuracy. Only now that high throughput sequencing is possible can we really begin to gather the volume of data needed to try and work development out in this way. It’s exciting to think about trying to look at development of multicellular organisms from a synthetic biology, modular point of view, but turning that theory into reality is likely to be extremely complex!

    1. We need not always require molecular data to mathematically model something but, in fact, models can hint where to look for the molecules. Alan Turing (1952), with no background in biology, proposed how a homogenous population of cells would give rise to a pattern of heterogeneous cells.

      At looking at development with a synthetic biology viewpoint, I think the complexity itself may pave the way to robust modules.

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