Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming

The use of computational models is increasingly expected to play an important role in predicting the behaviour of biological systems. Models are being sought at different scales of biological organisation namely: sub-cellular, cellular, tissue, organ, organism and ecosystem; with a view of identifying how different components are connected together, how they are controlled and how they behave when functioning as a system. Except for very simple biological processes, system identification from first principles can be extremely difficult. This has brought into focus automated techniques for constructing models using data of system behaviour. Such techniques face three principal issues: (1) The model representation language must be rich enough to capture system behaviour; (2) The system identification technique must be powerful enough to identify substantially complex models; and (3) There may not be sufficient data to obtain both the model's structure and precise estimates of all o...

• Type: Journal
• Year: 2008
• Where: JMLR
• Authors: Ashwin Srinivasan, Ross D. King
• Keywords: Biological, Complex Models, Computational Models, JMLR 2008