A Gaussian mixture model is used to learn spectral densities from 2DES experiments, enabling extraction of vibronic couplings, spectral extrapolation, and optimized experiment selection across simulated and experimental systems.
Nature Meth- ods16(4), 299–302 (Apr 2019)
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MetaboKG supplies a transformation workflow, semantic model based on PROV-O/SIO and domain ontologies, and Universal Annotation Identifier to enable graph-based integration and SPARQL queries over 680 GNPS molecular networking results.
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Streamlining Analysis and Design of Two-Dimensional Electronic Spectroscopy using Machine Learning
A Gaussian mixture model is used to learn spectral densities from 2DES experiments, enabling extraction of vibronic couplings, spectral extrapolation, and optimized experiment selection across simulated and experimental systems.
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MetaboKG: An Analysis-centric Knowledge Graph Framework for Untargeted Metabolomics
MetaboKG supplies a transformation workflow, semantic model based on PROV-O/SIO and domain ontologies, and Universal Annotation Identifier to enable graph-based integration and SPARQL queries over 680 GNPS molecular networking results.