molekylionet
Molekylionet is a conceptual framework for representing and analyzing molecular interaction networks as interconnected graphs that integrate data from experiments, simulations, and the scientific literature. It is used to model chemical processes at molecular scales, capturing both the static topology of interactions and, in extended forms, their dynamic behavior under varying conditions.
In a typical molekylionet, nodes correspond to molecular species and sometimes reactive intermediates; edges denote interactions
Implementation and tools involve data integration standards, ontologies, and graph databases. Modeling approaches range from static
Applications span drug discovery, enzyme mechanism studies, catalytic design, materials science, systems chemistry, and metabolic pathway
Challenges include data heterogeneity and quality, interoperability of formats, scalability to large networks, interpretability of complex