(272d) Mathematical Models in Biology: From Molecules to Life | AIChE

(272d) Mathematical Models in Biology: From Molecules to Life


Kaznessis, Y. - Presenter, University of Minnesota

A vexing question in the biological sciences is the following: can biological phenotypes be explained with mathematical models of molecules that interact according to physical laws? At the crux of the matter lies the doubt that humans can develop faithful mathematical representations of living organisms. We think there are two major reasons for this difficulty: First, biological systems are not only non-linear and often stochastic, but they possess an overwhelming number of variables. Consequently, although in principle these systems obey physical laws, there are insurmountable mathematical difficulties to develop tractable, first-principles models. Second, biology is a discipline in history: Dobzhansky's dictum that ?Nothing in biology makes sense except in the light of evolution? casts a long shadow on mathematical models of phenotypic complexity. Because, how exactly can we integrate thermodynamics with evolution? Is there then any hope that mathematics will ever be considered as indispensible a tool in the biosciences as in the physical sciences? We think there is. We believe that a synthetic biology research programme may liberate empiricism beyond the unaided human brain. Humans can now construct and piece together DNA sequences in order to design new biological systems and organisms. We can do this more quickly and less expensively than ever. Synthetic biology is the discipline that focuses on the construction of these novel biological systems. Synthetic biological systems confer three advantages that may help us make a plausible case for so ardent a vision, as to describe biology with mathematics: a) they are small and well-defined enough to be captured by universal yet tractable mathematical models; b) they are modular enough to string together and build logical and informational architectures that are the essence of living systems; c) they are to some extent our designs, not nature's, avoiding some of the difficulties of historical explanations. Armed with supercomputers and sophisticated mathematical models we can then investigate how information is transferred from molecules and their interactions, to cascades of gene regulatory relations, to emerging logical and informational architectures in bacteria. In the presentation we will explore the tractability of mathematical models that are founded on universal laws of thermodynamics and molecular biology. We will argue that computer simulations take on the role of tractable mathematics, bringing us one step closer to determining whether life's distinctiveness can be explained by the laws of chemistry and physics.

Kaznessis YN. Computational methods in synthetic biology. Biotechnol J. 2009;4(10):1392-405.