Literature DB >> 20051249

Concurrent growth of phenotypic features: a phenomenological universalities approach.

L Barberis1, C A Condat, A S Gliozzi, P P Delsanto.   

Abstract

Different physical features of an organism are often measured concurrently, because their correlations can be used as predictors of longevity, future health, or adaptability to an ecological niche. Since, in general, we do not know a priori if the temporal variations in the measured quantities are causally related, it may be useful to have a method that could help us to identify possible correlations and to obtain parameters that may vary from population to population. In this paper we develop a procedure that may detect underlying relationships. We do this by generalizing the recently introduced concept of phenomenological universalities to the complex field. In this generalization, allometric growth is described by a complex function, whose real and imaginary parts represent two phenotypic traits of the same organism. As particular solutions of the resulting problem, we obtain generalizations of the Gompertz and the von Bertalanffy-West growth equations. We then apply the procedure to two biological systems in order to show how to determine the existence of mutual interference between trait variations. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20051249     DOI: 10.1016/j.jtbi.2009.12.024

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  2 in total

1.  Dynamic Contrast-Enhanced MRI in the Study of Brain Tumors. Comparison Between the Extended Tofts-Kety Model and a Phenomenological Universalities (PUN) Algorithm.

Authors:  Maurizio Bergamino; Laura Barletta; Lucio Castellan; Gianluigi Mancardi; Luca Roccatagliata
Journal:  J Digit Imaging       Date:  2015-12       Impact factor: 4.056

2.  A novel approach to the analysis of human growth.

Authors:  Antonio S Gliozzi; Caterina Guiot; Pier Paolo Delsanto; Dan A Iordache
Journal:  Theor Biol Med Model       Date:  2012-05-17       Impact factor: 2.432

  2 in total

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