Laura Rosina Torres Ortega

The paper expands a bile acid and steroidal MS/MS spectral library across three repositories, capturing diverse structures and providing a resource for classifying unknown spectra.

The paper introduces arteMIS, a framework for optimizing molecular network parameters in metabolomics, showing improved network quality over default settings.

This paper introduces a method to assess the reliability of metabolite annotations in untargeted metabolomics by evaluating match reproducibility under spectral perturbation.

The paper improves MS2LDA for substructure discovery in mass spectrometry by enhancing speed and introducing automated annotation guidance, validated on chemical datasets.

This study examines how short wavelengths like UVB, UVA, and blue light affect the floral flavonoid metabolome of cannabis using a comparative metabolomics approach.