Title of article :
Constructing explanatory process models from biological data and knowledge
Author/Authors :
Langley، نويسنده , , Pat and Shiran، نويسنده , , Oren and Shrager، نويسنده , , Jeff and Todorovski، نويسنده , , Ljup?o and Pohorille، نويسنده , , Andrew، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2006
Abstract :
SummaryObjective
ress the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis regulation.
s
t both models and background knowledge in terms of processes that interact to account for behavior. We also describe IPM, an algorithm for inducing quantitative process models from such input.
s
onstrate IPM’s use both on photosynthesis and on a second domain, biochemical kinetics, reporting the models induced and their fit to observations.
sion
sider the generality of our approach, discuss related research on biological modeling, and suggest directions for future work.
Keywords :
Biochemical kinetic reactions , Computational scientific discovery , Inductive process modeling , Photosynthesis regulation
Journal title :
Artificial Intelligence In Medicine
Journal title :
Artificial Intelligence In Medicine