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Background
Lloyd Demetrius is a mathematician and theoretical biologist at the Max Planck Institute for Molecular Genetics in Berlin, Germany, and in the Department of Organismic and Evolutionary Biology at Harvard University. Demetrius earned a BA (1961) and MA (1964) in mathematics from Cambridge University in England, and a PhD (1967) from the University of Chicago.
Interests
Demetrius’ main research interests are the ergodic theory of dynamical systems and its applications to the analysis of biological processes at molecular, cellular and population levels; and quantum statistics as a formalism to investigate the dynamics of electron transport and proton transduction in cellular metabolism.
He is best known for the discovery of evolutionary entropy, a statistical parameter that characterizes Darwinian fitness in models of evolutionary processes at various levels of biological organization – molecular, organismic and cultural. Demetrius has also pioneered the application of the methodology of quantum mechanics to the study of allometric relations between metabolic rate and generation time in cells. This work is the mathematical basis for the analysis of cancer and neurodegenerative disorders as metabolic and bioenergetic diseases.
Sample Work
Publication
Game theory and evolution: finite size and absolute fitness measures
Demetrius, L. and Gundlach, V.M. (2000): Game theory and evolution: finite size and absolute fitness measures. Mathematical Biosciences, 168: 9 – 38 .
Publication
Directionality principles in thermodynamics and evolution
Demetrius, L. (1997): Directionality principles in thermodynamics and evolution. Proc. Natl. Acad. Sci. USA, 94: 3491 – 3498 .
Publication
Evolutionary formalism for products of positive random matrices
Arnold, L., Demetrius, L. and Gundlach, V.M. (1994): Evolutionary formalism for products of positive random matrices. The Annals of Applied Probability, Vol. 4, No. 3: 859 – 901
Publication
Statistical Mechanics and Population Biology
Demetrius, L. (1983): Statistical Mechanics and Population Biology. Journal of Statistical Physics, Vol. 30, No. 3: 709 – 753 .