Chemical Graph Transformation and Applications

Any computational method in chemistry must choose some level of precision in the modeling. One choice is made in the methods of quantum chemistry based on quantum field theory. While highly accurate, the methods are computationally very demanding, which restricts their practical use to single reactions of molecules of moderate size even when run on supercomputers. At the same time, most existing computational methods for systems chemistry and biology are formulated at the other abstraction extreme, in which the structure of molecules is represented either not at all or in a very rudimentary fashion that does not permit the tracking of individual atoms across a series of reactions.

In this talk, we present our on-going work on creating a practical modelling framework for chemistry based on Double Pushout graph transformation, and how it can be applied to analyse chemical systems. We will address important technical design decisions as well as the importance of methods inspired from Algorithm Engineering in order to reach the required efficiency of our implementation. We will present chemically relevant features that our framework provides (e.g. automatic atom tracing) as well as a set of chemical systems we investigated are currently investigating. If time allows we will discuss variations of graph transformation rule compositions and their chemical validity.

Video recording of the seminar on YouTube: click here!
Daniel Merkle
Daniel Merkle
Professor of Computer Science

Daniel Merkle received the Diploma degree in Computer Science and the PhD degree in Applied Computer Science from the University of Karlsruhe, Germany, in 1997 and 2002, respectively. He worked as an assistant professor with the Department of Computer Science, Leipzig, Germany, until April 2008. He has been an associate professor in the Department of Mathematics and Computer Science, University of Southern Denmark and became full professor in 2017. His group develops combinatorial and algorithmic approaches for Chemistry. E.g., they currently work with colleagues from Harvard Medical School and the University of Vienna in order to use graph transformation approaches for enzyme design.

Jakob Lykke Andersen
Jakob Lykke Andersen
Assistant Professor in Computer Science

Jakob Lykke Andersen is an assistant professor in the Department of Mathematics and Computer Science, University of Southern Denmark. He works on formal methods for modelling and analysing chemical systems (algorithmic cheminformatics) and combines it with algorithm engineering to obtain implementations that are useful in practice. He is in general interested in algorithmics (in particular graph algorithms) and generic programming.