Title :
Evolving Biological Behavior in Gene-Based Cellular Simulations
Author :
Phan, John H. ; Moffitt, Richard A. ; Stokes, Todd H. ; Wang, May D.
Author_Institution :
Georgia Inst. of Technol., Atlanta
Abstract :
Cellular automata (CA) have long been capable of producing life-like behavior such as complexity, communication and self-replication using simple rules. Despite these properties, CA and other discrete simulations have failed to achieve real-world utility in cancer research or developmental biology, largely because they do not conform to a rules model which is understandable by clinicians and biologists. We present a method to generate CA with a desired phenotypic behavior within a biologically-based family of rule sets modeling simple gene regulation in a cell cycle signaling pathway. Designing CA within this biological context ensures the interpretability of any emergent results, thus opening the door for applications in biomedicine such as tumor growth and angiogenesis. Rule sets are encoded in intuitive genome structures, which are co-evolved using a Genetic Algorithm (GA) with a fitness function chosen to reward Wolfram´s Type IV behavior. Results show the ability to generate interpretable type IV behavior in just a few hours on a desktop PC. This work is expected to have many applications including systems biology and cancer research.
Keywords :
biological techniques; blood vessels; cancer; cellular automata; cellular biophysics; genetic algorithms; genetics; molecular biophysics; replica techniques; tumours; Wolfram type IV property; angiogenesis; biologically-based family; biomedicine applications; cancer; cell cycle signaling pathway; cellular automata; discrete simulations; fitness function; gene regulation; gene-based cellular simulations; genetic algorithm; intuitive genome structures; life-like behavior; phenotypic property; self-replication; tumor growth; Bioinformatics; Biological information theory; Biological system modeling; Cancer; Cells (biology); Computational biology; Genetic algorithms; Genomics; Neoplasms; Signal generators; artificial life; biological simulation; cancer; cellular automata; gene regulation; genetic algorithms;
Conference_Titel :
Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-1509-0
DOI :
10.1109/BIBE.2007.4375609