Simulation of Biological Systems
CS 8803 SBS
Instructor: Greg Turk
Semester: Spring 2013
Time: 11:05 - 11:55pm, MWF
Location: Environmental Science and Technology L1125
Homework 1 (Life Cellular Automata)
- This first homework is due at the end of the second week of class.
Homework 2 (Flocking)
Homework 3 (Reaction-Diffusion)
Chapter 1 in Origins of Life.
Optional: Christopher Langton's
Edge of Chaos.
Chapter 2 in Origins of Life.
flocking of virtual
Chapter 3 in Origins of Life.
Metabolic pathways chart1
Wolfgang Banzhaf's self-organization in
Chapter 4 in Origins of Life.
Tim Hutton's self-reproducing simulated molecules.
2D version of protein folding.
on protein folding complexity.
Classic DNA paper by
Watson and Crick.
bubbling flask to produce amino acids.
genetic code is optimal.
Chapter 5 in Origins of Life.
Pattern formation by
Chapter 6 in Origins of Life.
The Genetic Algorithm.
Chapter 7 and 8 in Origins of Life.
Plant growth simulation with
voxel space automata.
Plant growth using
Creating branching patterns using
Chapter 9 in Origins of Life.
Chapter 10 in Origins of Life.
from Karl Sims.
from Frank Dellaert and Randall Beer.
Evolution and manufacturing of
from Tu and Terzopoulos.
Evolved flying creatures.
Chapter 11 in Origins of Life.
Thomas Ray's Tierra
system of evolving programs.
Robert Axelrod and the
Chapter 12 in Origins of Life.
Craig Reynolds on
Related Web Links
compiled by Craig Reynolds.
Mass-spring locomotion at sodaplay.
(Be sure your browser can run Java!)
virtual creatures from Karl Sims (locomotion and competition).
Dr. Prusinkiewicz's research on plant development.
(digital creatures that execute code) from Thomas Ray.
loops from Hiroki Sayama.
Artificial life links.
This course covers a broad array of techniques for computer
simulation of biological systems. The course material will draw from
biology, artificial life, robotics, computer graphics and other
areas. Some of the course topics include self-replication, artificial
chemistry, multi-cellular development, simulation of evolution,
automata, mass-spring simulators, L-systems for plant development,
animal locomotion (walking, swimming, jumping), flocking and herding
behavior in groups, predator/prey systems, parasites, and foraging
Students will carry out several programming projects during the
Basic programming skills are recommended for students entering the
but no previous background in biology is necessary. There will be
three or four small programming projects during the first part of the
course. During the second half, students will propose and work on a
large project of their choice. Projects can be done individually or
in teams of two students.
- self-replication (von Neumann, Christopher Langdon, others)
- complexity at edge of chaos
- artificial chemistry
- molecular hypercycles
- RNA folding
- DNA codon optimality
Membranes and Cells
- membrane formation
- cell models
- cell cytoskeletons
- immune systems
Cell aggregation (courtesy of Kurt Fleischer)
- multicellular development
- slime mold aggregation
- pattern formation
- gene cascades/networks
- cell simulation of development (Fleischer and Barr)
- L-systems for plant development
Plant growth (courtesy of Przemyslaw Prusinkiewicz)
- Dawkins on major events in evolution
- genetic algorithms
- blind watchmaker
- co-evolution (Karl Sims, Craig Reynolds, Danny Hillis)
- sexual selection
- modes of locomotion
- Braitenberg vehicles
- evolution of walking and hopping motion (Karl Sims)
- swimming (Terzopoulos)
Walking simulation (courtesy of Karl Sims)
Physics Simulation Techniques
- partial differential equations (PDE's)
- cellular automata (life, spiral waves, etc.)
- mass-spring systems
Tentacle motion (courtesy of Andrew Cantino)
- Prisoner's dilemma, tit-for-tat
- flocks, schools, swarms
- ant foraging
- digital creatures (Thomas Ray)
Flocking with collision avoidance (courtesy of Craig
Greg Turk's Home Page.