Integral biomathics: a post-Newtonian view into the logos of bios

Prog Biophys Mol Biol. 2010 Jun-Jul;102(2-3):85-121. doi: 10.1016/j.pbiomolbio.2010.01.005. Epub 2010 Feb 8.

Abstract

This work is an attempt for a state-of-the-art survey of natural and life sciences with the goal to define the scope and address the central questions of an original research program. It is focused on the phenomena of emergence, adaptive dynamics and evolution of self-assembling, self-organizing, self-maintaining and self-replicating biosynthetic systems viewed from a newly-arranged perspective and understanding of computation and communication in the living nature. The author regards this research as an integral part of the emerging discipline of nature-inspired or natural computation, i.e. computation inspired by or occurring in nature. Within this context, he is interested in studies which represent a significant departure from traditional theories about complex systems and self-organization, emergent phenomena and artificial biology. In particular, these include non-conventional approaches exploring the aggregation, composition, growth and development of physical forms and structures, autopoiesis along with the associated abstract information structures and processes. This paper provides a critical review of the major assumptions which guide the development of modern computer science and engineering towards emulating biological systems. For this purpose, the author explores the potential and the virtues of biology to reshape contemporary science. The goal of this survey is to discuss the present state of natural and engineering sciences in the light of a necessary paradigm change in the structure and methodology of research and deliver some insights for developing a new kind of integral science based on the principles for dynamic interdependence of the constituting disciplines and on the evolving relationships among them.

Publication types

  • Review

MeSH terms

  • Animals
  • Computational Biology*
  • Computer Simulation
  • Mathematical Concepts*
  • Models, Biological*