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https://doi.org/10.4203/ccp.84...
Article . 2009 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2006
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Probabilistic Regulatory Networks: Modelling Genetic Networks

Authors: Avino-Diaz, Maria A.; Moreno, Oscar;

Probabilistic Regulatory Networks: Modelling Genetic Networks

Abstract

We describe here the new concept of $ε$-Homomorphisms of Probabilistic Regulatory Gene Networks(PRN). The $ε$-homomorphisms are special mappings between two probabilistic networks, that consider the algebraic action of the iteration of functions and the probabilistic dynamic of the two networks. It is proved here that the class of PRN, together with the homomorphisms, form a category with products and coproducts. Projections are special homomorphisms, induced by invariant subnetworks. Here, it is proved that an $ε$-homomorphism for 0

8 pages, 2 figures, International Congress of Matematicians, to be published in Proceedings of the Fifth International Conference on Engineering Computational Technology, 2006, Las Palmas, Gran Canaria

Keywords

Genomics (q-bio.GN), FOS: Biological sciences, FOS: Mathematics, Quantitative Biology - Genomics, Dynamical Systems (math.DS), Mathematics - Dynamical Systems

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selected citations
These citations are derived from selected sources.
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!
0
Average
Average
Average
Green