CONTROL IN BIOLOGICAL SYSTEMS

                Seth Michelson, Roche Bioscience, MS S1-137
                  3401 Hillview Ave, Palo Alto, CA 94303

     While mathematical theory, simulation, numerical analysis,
and statistical analysis of mechanical systems has been developed
within the engineering curriculum for years, extension of these
techniques to biological systems is relatively new.  With the
advent of sophisticated computing technologies, mathematical
models in biology and medicine have grown to a point that there
is now a reasonable process in place which marries biomedical
experimentation to systems and control theory. 
     Biology requires homeostasis; chaos is probably a fatal
state.  Excitation and suppression of intercellular signalling,
up- and down-regulation of signal processing elements (e.g.,
receptors or second messenger systems), and on/off signal pro-
cessing at the genetic level all provide the exquisite controls
needed to keep an organism balanced and still flexible enough to
respond to hostile and variable environments.  In this minitrack,
we will preview four contributions, each dealing with one of
these facets of biological control:  

   A Biomathematical Model to Predict Bone Healing - Eberhard
Hofer, University. of ULM, Germany.
  A Parallel Computational Model of Attention and Saccade Genera-
tion in the Human Visual System - Barnabas Takacs, George Mason
University, Virginia.
   A New Mathematical Model of Slow-Binding Enzyme Inhibition -
Ondine Callan and David Sweeny, Roche Bioscience, Palo Alto,
California
  Biological Control in Tumor Growth - Seth Michelson, Roche
Bioscience, Palo Alto, California.