Search Results for author:
Found 4 papers, 1 papers with code
Simulating Petri nets with Boolean Matrix Logic Programming
However, logic programs struggle to deal with extensive Petri nets due to the limitations of high-level symbol manipulations.
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models
Techniques to autonomously drive research have been prominent in Computational Scientific Discovery, while Synthetic Biology is a field of science that focuses on designing and constructing new biological systems for useful purposes.
Human Comprehensible Active Learning of Genome-Scale Metabolic Networks
An important application of Synthetic Biology is the engineering of the host cell system to yield useful products.
Automated Biodesign Engineering by Abductive Meta-Interpretive Learning
The application of Artificial Intelligence (AI) to synthetic biology will provide the foundation for the creation of a high throughput automated platform for genetic design, in which a learning machine is used to iteratively optimise the system through a design-build-test-learn (DBTL) cycle.
