Mathematical Modeling of Complex Biological Systems: A Kinetic Theory Approach (Modeling and Simulation in Science, Engineering and Technology)

Bellouquid, Abdelghani; Delitala, Marcello

ISBN 10: 0817643958 / ISBN 13: 9780817643959

Verlag: Birkhäuser, 2006

Beschreibung

Birkhaeuser Verlag; Boston, 2006. Hardcover. A Near Fine, binding firm, interior and extremities tidy, minimal handling marks, book appears unread, bit of crimping to spine edges, small scratch mark mid rear board near spine, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 188pp., glossary, bibliography, indexed. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

Bestandsnummer des Verkäufers SKU1037395

Bibliografische Details

• Titel: Mathematical Modeling of Complex Biological Systems: A Kinetic Theory Approach (Modeling and Simulation in Science, Engineering and Technology)
• Verlag: Birkhäuser
• Erscheinungsjahr: 2006
• Sprache: Englisch
• ISBN-10: 0817643958
• ISBN-13: 9780817643959
• Einband: hardcover
• Zustand: As New
• Verkäuferkataloge:
  • Math Text Books

Über diesen Titel

Inhaltsangabe

This book describes the evolution of several socio-biological systems using mathematical kinetic theory. Specifically, it deals with modeling and simulations of biological systems whose dynamics follow the rules of mechanics as well as rules governed by their own ability to organize movement and biological functions. It proposes a new biological model focused on the analysis of competition between cells of an aggressive host and cells of a corresponding immune system. Proposed models are related to the generalized Boltzmann equation. The book may be used for advanced graduate courses and seminars in biological systems modeling.

Über die Autorin bzw. den Autor

This book describes the evolution of several socio-biological systems using mathematical kinetic theory. Specifically, it deals with modeling and simulations of biological systems―comprised of large populations of interacting cells―whose dynamics follow the rules of mechanics as well as rules governed by their own ability to organize movement and biological functions. The authors propose a new biological model for the analysis of competition between cells of an aggressive host and cells of a corresponding immune system.

Because the microscopic description of a biological system is far more complex than that of a physical system of inert matter, a higher level of analysis is needed to deal with such complexity. Mathematical models using kinetic theory may represent a way to deal with such complexity, allowing for an understanding of phenomena of nonequilibrium statistical mechanics not described by the traditional macroscopic approach. The proposed models are related to the generalized Boltzmann equation and describe the population dynamics of several interacting elements (kinetic populations models).

The particular models proposed by the authors are based on a framework related to a system of integro-differential equations, defining the evolution of the distribution function over the microscopic state of each element in a given system. Macroscopic information on the behavior of the system is obtained from suitable moments of the distribution function over the microscopic states of the elements involved. The book follows a classical research approach applied to modeling real systems, linking the observation of biological phenomena, collection of experimental data, modeling, and computational simulations to validate the proposed models. Qualitative analysis techniques are used to identify the prediction ability of specific models.

The book will be a valuable resource for applied mathematicians as well asresearchers in the field of biological sciences. It may be used for advanced graduate courses and seminars in biological systems modeling with applications to collective social behavior, immunology, and epidemiology.