Knowledge-based simulation of DNA metabolism: prediction of enzyme action.
We have developed a knowledge-based simulation of DNA metabolism that accurately predicts the actions of enzymes on DNA under a large number of environmental conditions. Previous simulations of enzyme systems rely predominantly on mathematical models. We use a frame-based representation to model enzymes, substrates and conditions. Interactions between these objects are expressed using production rules and an underlying truth maintenance system. The system performs rapid inference and can explain its reasoning. A graphical interface provides access to all elements of the simulation, including object representations and explanation graphs. Predicting enzyme action is the first step in the development of a large knowledge base to envision the metabolic pathways of DNA replication and repair.
Brutlag
D L
DL
Department of Biochemistry, Stanford University School of Medicine, CA 94305.
Galper
A R
AR
Millis
D H
DH
D000249:Adenosine Monophosphate / Q000378:metabolism; D001185:Artificial Intelligence; D003198:Computer Simulation; D011088:DNA Ligases / Q000378:metabolism; D004256:DNA Polymerase I / Q000378:metabolism; D004260:DNA Repair; D004261:DNA Replication; D004926:Escherichia coli / Q000201:enzymology / Q000235:genetics; D008954:Models, Biological; D009243:NAD / Q000378:metabolism; D014584:User-Computer Interface
D009243:NAD; D000249:Adenosine Monophosphate; D004256:DNA Polymerase I; D011088:DNA Ligases