Constructing explanatory process models from biological data and knowledge

We address the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis regulation. We cast 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, and we demonstrate its use both on photosynthesis and on a second domain, biochemical kinetics. In closing, we consider the generality of our approach, discuss related research on biological modeling, and suggest directions for future work. Keywords Computational scientific discovery, Inductive process modeling, Photosynthesis regulation, Biochemical kinetic reactions 

• Type: Journal
• Year: 2006
• Where: ARTMED
• Authors: Pat Langley, Oren Shiran, Jeff Shrager, Ljupco Todorovski, Andrew Pohorille
• Keywords: ARTMED 2006, Biochemical Kinetic, Candidate Biological Processes, Photosynthesis