Life Sciences and Bio-Computing
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Artificial Life's second business division for Life Science Applications focusses mainly on applications of its technology and algorithms in health care, biotech, pharmaceutics, genomics, proteomics, epidemiology, stem cell research and similar Life Science areas.
On this page we show various potential and factual uses of our technology and simulation algorithms. Artificial Life develops customized solutions for its clients based on these tools and products and other intellectual property.
Further details and information is available at:
info@artificial-life.com.
Stem Cell Simulator
This is a computationally intensive, real-time simulation that shows the formation of skin tissue from several epithelial stem cells. The simulation runs in 3 dimensions and the viewpoint can be altered to gain a user-defined perspective by clicking in the main render-window and dragging in a desired direction.
Computational Epidemics Using Cellular Automata
In this demo we have applied cellular automata to simulate the spread of certain diseases in a geographic region such as the United States. An "infection" is inserted at a user-defined location. Neighborhoods defined by travel routes determine what geographical patterns of infections will result. The simulation can be used in combination with optimization techniques to determine what kind of traffic barriers or re-routing could reduce the risk for specific areas. The simulation may also be used to analyze which locations are less likely to be affected after an attack with biological weapons. Please be aware that these simulations are highly simplified versions of a real threat-analysis simulation.
3D Cellular Automata
With this demonstration of cellular automata we show that a few simple rules of neighborhood relationships can lead to an evolution of very complex behavior patterns if a population of similar neighbors interact with each other. Play with our 3-dimensional Java-based cellular automata demo.
Simulations of the Gene Regulatory System
In this demo we simulate the feedback processes in a gene regulatory system in which genes regulate and influence the activity of other genes. The genes are represented as arrays on a chromosome. Their allele values are restricted to binary 0/1 values (black/white). Each gene receives input from exactly two other genes which are randomly chosen. When initialized with a random activity pattern, these gene regulatory feedback networks generate highly complex iterations resulting in certain loops. These loops may be understood as abstract representations of cell types as the loops represent attractors of the feedback system. The length and number of these cycles is of importance and can be analyzed in a pop up window. The cycles can be influenced by the random initialization as well as by the Boolean functions chosen to calculate the successors of a state. Literature refers to these kinds of automata also as NK Random Boolean Networks which have been most profoundly studied by Stuart Kauffman.
1D and 2D Cellular Automata
Here you can see one-dimensional and two-dimensional cellular automata simulations and the patterns that may emerge from application of certain neighborhood rules. The rules stem from models such as the game of Life and Sandpile model. Play with our 1-dimensional and 2-dimensional Java-based cellular automata demos.
Lindenmayer Systems: Pattern Generator and Plant Generator
The concept of Lindenmayer Systems represents an elegant mathematical tool for modeling plant growth and structure. The primary idea used in the model is the notion of self-similarity, where an object is constructed using numerous parts that are structurally similar to the whole. This permits the use of a very elegant and concise mathematical representation of the model, which consists of a small set of production rules.
Stock Market Simulation
The primary aim of this Java-based simulation of a stockmarket is to use a multitude of agents, in a manner very similar to the classical cellular automata approach, whose decisions to buy, sell or hold on to stocks, and the prices at which to buy or sell, are described by a small set of simple rules. The resulting market shows a variety of different trends, which depend on the initial state of the system.
Cockroaches Versus Vacuum Cleaners
A Java-based graphical visualization of the interaction between predator and prey. In this example, the different requirements for predator-prey interaction, such as predator growth triggered by the prey population, predator mortality due to prey shortage, growth of prey due to availability of food, and the death of prey due to predators and due to the shortage of food, have all been captured.
