Author

Maria Sorokina

Friedrich Schiller University JenaORCID 0000-0001-9359-7149Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 4

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 4 Approach:machine learning (classical)· 1 Assay:metabolomics· 1 Assay:metagenomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Christoph SteinbeckiD· 3 shared Achim ZielesnyiD· 1 shared Adriano RutziD· 1 shared Alberto M. R. DávilaiD· 1 shared Arnaud GaudryiD· 1 shared Bruno Gabriel Nascimento AndradeiD· 1 shared Daniel MietcheniD· 1 shared Egon WillighageniD· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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3 shared papersBioinformatics

Christoph SteinbeckORCID

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Author profile →

4 papers

Recent·Most cited

MAW - The Reproducible Metabolome Annotation Workflow for Untargeted Tandem Mass Spectrometry

Mahnoor Zulfiqar, Luiz M. R. Gadelha Jr., Christoph Steinbeck, Maria Sorokina, Kristian Peters

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

Journal of Cheminformatics · Mar 4, 2023Peer-reviewedBioinformatics

The LOTUS Initiative for Open Natural Products Research: Knowledge Management through Wikidata

Adriano Rutz, Maria Sorokina, Jakub Galgonek, Daniel Mietchen, Egon Willighagen, Arnaud Gaudry, James G. Graham, Ralf Stephan, Roderic Page, Jiřı́ Vondrášek, Christoph Steinbeck, Guido F. Pauli, Jean‐Luc Wolfender, Jonathan I. Bisson, Pierre‐Marie Allard

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.

eLife · Mar 23, 2022Peer-reviewedBioinformatics

Description and analysis of glycosidic residues in the largest open natural products database

Jonas Schaub, Achim Zielesny, Christoph Steinbeck, Maria Sorokina

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

Biomolecules · Mar 24, 2021Peer-reviewedBioinformatics

Global ocean resistome revealed: exploring Antibiotic Resistance Genes (ARGs) abundance and distribution on TARA oceans samples through machine learning tools

Rafael R. C. Cuadrat, Maria Sorokina, Bruno Gabriel Nascimento Andrade, Tobias Goris, Alberto M. R. Dávila

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.

GigaScience · May 1, 2020Peer-reviewedBioinformatics