Managing Complexity, Reducing Perplexity: Modeling Biological Systems Softcover reprint of the original 1st ed. 2014 Edition

Managing Complexity, Reducing Perplexity: Modeling Biological Systems Softcover reprint of the original 1st ed. 2014 Edition book cover

Managing Complexity, Reducing Perplexity: Modeling Biological Systems Softcover reprint of the original 1st ed. 2014 Edition

Author(s): Marcello Delitala (Editor), Giulia Ajmone Marsan

  • Publisher: Springer
  • Publication Date: September 17, 2016
  • Edition: Softcover reprint of the original 1st ed. 2014
  • Language: English
  • Print length: 151 pages
  • ISBN-10: 3319352008
  • ISBN-13: 9783319352008

Book Description

”Managing Complexity, Reducing Perplexity” is devoted to an overview of the status of the art in the study of complex systems, with particular focus on the analysis of systems pertaining to living matter. Both senior scientists and young researchers from diverse and prestigious institutions with a deliberately interdisciplinary cut were invited, in order to compare approaches and problems from different disciplines. The common aim of the contributions was to analyze the complexity of living systems by means of new mathematical paradigms that are more adherent to reality and which are able to generate both exploratory and predictive models that are capable of achieving a deeper insight into life science phenomena.

Editorial Reviews

From the Back Cover

This book is devoted to an overview of the status of the art in the study of complex systems, with particular focus on the analysis of systems pertaining to living matter. Both senior scientists and young researchers from diverse and prestigious institutions with a deliberately interdisciplinary cut were invited, in order to compare approaches and problems from different disciplines. The common aim of the contributions is to analyze the complexity of living systems by means of new mathematical paradigms that are more adherent to reality and which are able to generate both exploratory and predictive models that are capable of achieving a deeper insight into life science phenomena.

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