This is a contributed topic entry on computer simulations and automata theory applications.
0.1 Computer simulations and automata theory applications in life sciences, theoretical
biophysics, medicine and mathematical medicine
The applications of computers to biological and biomedical problem solving go back to the very
beginnings of computer science, automata theory, and mathematical biology. With the advent of
more versatile and powerful computers, biological and biomedical applications of computers have
proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of
all developments in this field. Limitations of computer simulations in biology have also come
under close scrutiny, and claims have been made that biological systems have limited
information processing power [3]. Such general conjectures do not, however, deter biologists
and biomedical researchers from developing new computer applications in biology and
medicine. Microprocessors are being widely employed in biological laboratories both for
automatic data acquisition/processing and modeling; one particular area, which is of great
biomedical interest, involves fast digital image processing and is already established for
routine clinical examinations in radiological and Nuclear Medicine centers, Powerful
techniques for biological research are routinely employing dedicated, on-line microprocessors
or array processors; among such techniques are: Fourier-transform nuclear magnetic
resonance (NMR), NMR imaging (or tomography), x-ray tomography, X-ray diffraction,
high performance liquid chromatography, differential scanning calorimetry and mass
spectrometry. Networking of laboratory microprocessors linked to a central, large memory
computer is the next logical step in laboratory automation. Previously unapproachable
problems, such as molecular dynamics of solutions, many-body interaction calculations and
statistical mechanics of biological processes are all likely to benefit from the increasing
access to the new generation of ”supercomputers”. In view of the large number, diversity
and complexity of computer applications in biology and medicine, we could not review
in any degree of detail all computer applications in these fields; instead, we shall be
selective and focus our discussion on suggestive computer models of biological systems
and those fundamental aspects of computer applications that are likely to continue to
make an impact on biological and biomedical research. Thus, we shall consider unifying
trends in mathematics, mathematical logics and computer science that are relevant to
computer modeling of biological and biomedical systems. The latter are pitched at a
more formal, abstract level than the applications and, therefore, encompass a number of
concepts drawn from the abstract theory of sets and relations, network theory, automata
theory, Boolean and n-valued logics, abstract algebra, topology and category theory.
The present analysis of Relational Theories in biology and computer simulation has
also inspired a number of new results which are presented here as ”Conjectures” since
their proofs are too lengthy and too technical to be included in this review. In order to
maintain a self-contained presentation-the definitions of the main concepts are given, with
the exception of a minimum of simple mathematical concepts. The purpose of these
theoretical sections is to provide the basis for approaching a number of basic biological
questions: (1) What are the essential characteristics of a biological organism as opposed to
an automaton? (2) Are biological systems recursively computable? (3) What is the
structure of the simplest (primordial) organism? (4) What are the basic structures of
neural and genetic networks? (5) What are the common properties of classes of biological
organisms? (6) Which system representations are adequate for biodynamics? (7) What is the
optimal strategy for modifying an organism through genetic engineering? (8) What is the
optimal simulation of a biological system with a digital or analog computer? (9) What is
life?