Algorithmic Cheminformatics Meets Causality Analysis

The project is funded by the Independent Research Fund Denmark, Natural Sciences. The project combines the expertise from the Algorithmic Cheminformatics Group at IMADA (Daniel Merkle, Rolf Fagerberg, Jakob L. Andersen) and from the Fontana Lab at Harvard Medical School (Walter Fontana).

The project

We will in this project integrate and unify the theories, algorithmic methods, and efficient implementations of two existing computational frameworks: MØD, which is based on graph transformation formalisms, and Kappa, which builds on concurrency theory. Both frameworks aim at analyzing large and complex chemical and biological reaction networks. They share their rigorous foundation on category theory, while having different strengths: MØD has a chemically quite explicit modeling level (representing molecules as undirected graphs), which e.g. allows for tracing individual atoms across many reactions. Kappa is aimed at studying causality in networks, which allows the concept of reaction pathways to be rigorously defined and studied. Combining these abilities will allow for foundational studies of, and computational solutions to, many questions in systems chemistry and biology, two areas in dire need of better computational methodologies due to the complexity of the involved networks.