A Temporal Graph Model to Predict Chemical Transformations in Complex Dissolved Organic Matter.

ABSTRACT: Dissolved organic matter (DOM) is a complex mixture of thousands of natural molecules that undergo constant transformation in the environment, such as sunlight induced photochemical reactions. Despite molecular level resolution from ultrahigh resolution mass spectrometry (UHRMS), trends of mass peak intensities are currently the only way to follow photochemically induced molecular changes in DOM. Many real-world relationships and temporal processes can be intuitively modeled using graph data structures (networks). Graphs enhance the potential and value of AI applications by adding context and interconnections allowing the uncovering of hidden or unknown relationships in data sets. We use a temporal graph model and link prediction to identify transformations of DOM molecules in a photo-oxid

SUBMITTER: Plamper P 

PROVIDER: S-EPMC10666529 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature