Work

Beyond mutation matrices

Year: 1998

Type: conference-paper

Abstract: We describe a model for characterizing site mutations in evolving proteins.By representing the fitness of each of the amino acids as a function of the physical-chemical properties of that amino acid, and constructing mutation matrices based on Boltzmann statistics and Metropolis kinetics, we are able to greatly reduce the number of adjustable parameters.This allows us to include site heterogeneity in the model, as well as to optimize the model for specific protein types.We demonstrate the applicability of the model by investigating the phylogenetic relationship between various subtypes of HIV-I.

Source: Research in Computational Molecular Biology

DOI: 10.1145/279069.279107

Authors: Jeffrey M. Koshi, David P. Mindell, Richard A. Goldstein

Institution: University of Michigan

Language: English

Topic: Evolution and Genetic Dynamics

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze

Funders: National Science Foundation, National Institutes of Health

Award: Supercomputing Resource for Study of Biomacromolecular Structure and Dynamics