Maria Sorokina

This study uses metabolomics and transcriptomics to analyze interactions between two marine microalgae in mono-cultures and co-cultures, revealing metabolic communication and cellular repair mechanisms.

MAW automates metabolome annotation using LC-MS2 data by integrating spectral databases and tools, improving candidate ranking and reproducibility.

The paper introduces the LOTUS initiative, which curates and shares 750,000+ structure-organism pairs via Wikidata to improve data interoperability and knowledge management in natural products research.

The paper describes and analyzes glycosidic residues in the COCONUT database, highlighting their diversity and importance in drug discovery.

This study uses machine learning to analyze metagenomic data from the TARA Oceans project to identify and characterize antibiotic resistance genes (ARGs) in marine environments, revealing their abundance, distribution, and potential for horizontal gene transfer.