Optimization of cellular metabolism
Cellular metabolism is one of the most measured phenomena and can be modeled by many formalisms, approaches and their combinations. We use just some of them.
Different applications of artificial intelligence are applicable in case of huge solution spaces of a scientific or practical question. The growing number and size of different databases give more and more data to be evaluated for application in different biotechnological solutions. Omics data add another dimension to the analysis of solution space.
That leads to application of different sub-fields of artificial intelligence as machine learning, deep learning, neural networks to help get valuable information from big data. Our main interest is in the application of artificial intelligence in the selection of most appropriate metabolic engineering design for particular substrate-product pairs including the selection of the most appropriate organism and necessary modifications to reach good compromise in different sustainability aspects.