Modelling the Dynamics of Biological Systems: Nonlinear Phenomena and Pattern Formation (Springer Series in Synergetics)

ISBN 10: 3642792928 / ISBN 13: 9783642792922

Edité par Springer, 2011

A propos de cet article

Like New.

N° de réf. du vendeur ERICA79636427929286

Détails bibliographiques

• Titre: Modelling the Dynamics of Biological Systems: Nonlinear Phenomena and Pattern Formation (Springer Series in Synergetics)
• Éditeur: Springer
• Date de parution: 2011
• Langue: anglais
• ISBN à 10 chiffres: 3642792928
• ISBN à 13 chiffres: 9783642792922
• Reliure: Paperback
• État de l'article: Like New
• Type de livre: book

A propos de ce titre

Synopsis

The development of a proper description of the living world today stands as one of the most significant challenges to physics. A variety of new experimental techniques in molecular biology, microbiol- ogy, physiology and other fields of biological research constantly expand our knowledge and enable us to make increasingly more detailed functional and structural descriptions. Over the past decades, the amount and complexity of available information have multiplied dramatically, while at the same time our basic understanding of the nature of regulation, behavior, morphogenesis and evolution in the living world has made only modest progress. A key obstacle is clearly the proper handling of the available data. This requires a stronger emphasis on mathematical modeling through which the consistency of the adopted explanations can be checked, and general princi- ples may be extracted. As an even more serious problem, however, it appears that the proper physical concepts for the development of a theoretically oriented biology have not hitherto been available. Classical mechanics and equilibrium thermody- namics, for instance, are inappropriate and useless in some of the most essen- tial biological contexts. Fortunately, there is now convincing evidence that the concepts and methods of the newly developed fields of nonlinear dynam- ics and complex systems theory, combined with irreversible thermodynamics and far-from-equilibrium statistical mechanics will enable us to move ahead with many of these problems.