Title :
Using fuzzy measures to group cycles in metabolic networks
Author :
Dickerson, Julie ; Cox, Zach
Author_Institution :
Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
Abstract :
This paper describes part of a modeling tool, called FCModeler, for exploring metabolic networks that displays and finds structural relationships in graphs. Nodes of the map represent specific biochemicals such as proteins, RNA, and small molecules, or stimuli, such as light, heat, or nutrients. Edges of the map capture regulatory and metabolic relationships found in biological systems. These relationships are established by domain experts and the biological literature. Automated cycle analysis finds sets of connected nodes in a metabolic network. Families of interconnected cycles show how metabolic cycles interact with one another. These cycle families are formed using fuzzy measure theory.
Keywords :
biochemistry; directed graphs; fuzzy set theory; molecular biophysics; search problems; FC modeler; RNA; automated cycle analysis; biochemicals; biological literature; biological systems; connected nodes; fuzzy measure theory; metabolic cycles; metabolic networks; metabolic relationships; modeling tool; proteins; regulatory relationships; small molecules; stimuli; structural graphs; Biochemistry; Displays; Intelligent networks; Particle measurements; Search problems;
Conference_Titel :
Fuzzy Information Processing Society, 2003. NAFIPS 2003. 22nd International Conference of the North American
Print_ISBN :
0-7803-7918-7
DOI :
10.1109/NAFIPS.2003.1226789