In silico evolution of functional modules in biochemical networks.
Understanding the large reaction networks found in biological systems is a daunting task. One approach is to divide a network into more manageable smaller modules, thus simplifying the problem. This is a common strategy used in engineering. However, the process of identifying biological modules is still in its infancy and very little is understood about the range and capabilities of motif structures found in biological modules. In order to delineate these modules, a library of functional motifs has been generated via in silico evolution techniques. On the basis of their functional forms, networks were evolved from four broad areas: oscillators, bistable switches, homeostatic systems and frequency filters. Some of these motifs were constructed from simple mass action kinetics, others were based on Michaelis-Menten kinetics as found in protein/protein networks and the remainder were based on Hill equations as found in gene/protein interaction networks. The purpose of the study is to explore the capabilities of different network architectures and the rich variety of functional forms that can be generated. Ultimately, the library may be used to delineate functional motifs in real biological networks.
Paladugu
S R
SR
Keck Graduate Institute, 535 Watson Drive, Claremont, CA 91711, USA.
Chickarmane
V
V
Deckard
A
A
Frumkin
J P
JP
McCormack
M
M
Sauro
H M
HM
D000465:Algorithms; D000818:Animals; D001671:Biochemistry / Q000379:methods*; D001683:Biological Clocks / Q000502:physiology*; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D019143:Evolution, Molecular; D006801:Humans; D008954:Models, Biological; D008957:Models, Genetic; D009097:Multienzyme Complexes / Q000502:physiology*; D015398:Signal Transduction / Q000502:physiology*
D009097:Multienzyme Complexes