Exploring Chemical Reaction Space with Reaction Difference Fingerprints and Parametric t-SNE.

ABSTRACT: Humans prefer visual representations for the analysis of large databases. In this work, we suggest a method for the visualization of the chemical reaction space. Our technique uses the t-SNE approach that is parameterized using a deep neural network (parametric t-SNE). We demonstrated that the parametric t-SNE combined with reaction difference fingerprints could provide a tool for the projection of chemical reactions on a low-dimensional manifold for easy exploration of reaction space. We showed that the global reaction landscape projected on a 2D plane corresponds well with the already known reaction types. The application of a pretrained parametric t-SNE model to new reactions allows chemists to study these reactions in a global reaction space. We validated the feasibility of this approa

SUBMITTER: Andronov M 

PROVIDER: S-EPMC8600617 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature