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SIAM Journal on Applied Mathematics
Article . 1978 . Peer-reviewed
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Genetic Algebras Considered as Elements in a Vector Space

Genetic algebras considered as elements in a vector space
Authors: Ivar Heuch;

Genetic Algebras Considered as Elements in a Vector Space

Abstract

For studying certain problems in mathematical population genetics one may introduce nonassociative linear algebras specifying the probability distribution of offspring genotypes given the genotypes of the parents. In this paper it is pointed out that it may be useful to regard these algebras as vectors in a larger space. The set of baric algebras with a fixed weight function and the set of genetic algebras with a fixed canonical basis are shown to form flats in this space. Possible choices of a suitable basis are discussed for the subspace of algebras corresponding to linked autosomal loci. It is shown that there exists in some situations a particular basis of algebras with genetic interpretation such that all other algebras of possible genetic significance can be expressed as convex combinations of the basis elements.

Keywords

Genetic Interpretation, Genetic Algebras, Basic Algebras, Nonassociative Linear Algebras, Mathematical Population Genetics, Genetics and epigenetics, Basis, Other nonassociative rings and algebras

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Average
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