Hello everybody! First post here, just a brief introduction:
My name is Federico and I’m a Computer Science PhD student dealing with Machine Learning in the field of Material Science.
Led by a recent interest in GNNs, I’ve started to figure out some useful toolboxes /APIs to deal with graph-data structures.
Basically, what I’m trying to understand for now is, if I start with a typical pandas dataframe consisting of several chemical formulas (Strings), is it possible to convert them in a graph data format, and then featurizing these data graphs, for example getting node features to be used in a Graph Convolutional Network? If yes, may you give me some suggestions on how to do that?
For now (outside of GNNs context) I’ve just done some practice with Matminer toolbox, converting (strings) formulas into ‘Composition’ objects and then featurizing them to obtain a variety of chemical/compositional/physical properties, but not sure at all how to do this for graph-type data.
Thank you all,