Some nonlinear challenges in biology -
Mosconi, Francesco and Julou, Thomas and Desprat, Nicolas and Sinha, Deepak Kumar and Allemand, Jean-Francois and Croquette, Vincent and Bensimon, DavidNONLINEARITY 21,
T131-T147 (2008) LPS
Abstract : Driven by a deluge of data, biology is undergoing a transition to a more
quantitative science. Making sense of the data, building new models,
asking the right questions and designing smart experiments to answer
them are becoming ever more relevant. In this endeavour, nonlinear
approaches can play a fundamental role. The biochemical reactions that
underlie life are very often nonlinear. The functional features
exhibited by biological systems at all levels (from the activity of an
enzyme to the organization of a colony of ants, via the development of
an organism or a functional module like the one responsible for
chemotaxis in bacteria) are dynamically robust. They are often
unaffected by order of magnitude variations in the dynamical parameters,
in the number or concentrations of actors (molecules, cells, organisms)
or external inputs (food, temperature, pH, etc). This type of structural
robustness is also a common feature of nonlinear systems, exemplified by
the fundamental role played by dynamical fixed points and attractors and
by the use of generic equations (logistic map, Fisher-Kolmogorov
equation, the Stefan problem, etc.) in the study of a plethora of
nonlinear phenomena. However, biological systems differ from these
examples in two important ways: the intrinsic stochasticity arising from
the often very small number of actors and the role played by evolution.
On an evolutionary time scale, nothing in biology is frozen. The systems
observed today have evolved from solutions adopted in the past and they
will have to adapt in response to future conditions. The evolvability of
biological system uniquely characterizes them and is central to biology.
As the great biologist T Dobzhansky once wrote: `nothing in biology
makes sense except in the light of evolution'.