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Axioms 2014, 3(1), 109-118; doi:10.3390/axioms3010109

Optimization Models for Reaction Networks: Information Divergence, Quadratic Programming and Kirchhoff’s Laws

1
IME-USP, Institute of Mathematics and Statistics of the University of São Paulo, Rua do Matão, 1010, Cidade Universitária, 05508-090, São Paulo, Brazil
2
EACH-USP, School of Arts, Sciences and Humanities of the University of São Paulo, Av. Arlindo Béttio, 1000, Ermelino Matarazzo, 03828-000, São Paulo, Brazil
*
Author to whom correspondence should be addressed.
Received: 4 November 2013 / Revised: 19 February 2014 / Accepted: 21 February 2014 / Published: 5 March 2014
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Abstract

This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science. View Full-Text
Keywords: affinity; conservation laws; entropy and quadratic optimization; mass-action law; ontology alignment; stoichiometry; variational principles affinity; conservation laws; entropy and quadratic optimization; mass-action law; ontology alignment; stoichiometry; variational principles
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Stern, J.M.; Nakano, F. Optimization Models for Reaction Networks: Information Divergence, Quadratic Programming and Kirchhoff’s Laws. Axioms 2014, 3, 109-118.

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