Author

Karin Schork

Ruhr University BochumORCID 0000-0003-3756-4347Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:database / resource· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Martin EisenacheriD· 2 shared Michael TurewicziD· 2 shared Anika Frericks-Zipper· 1 shared Jörg RahnenführeriD· 1 shared Julian UszkoreitiD· 1 shared Katrin MarcusiD· 1 shared Markus StepathiD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 15 mutual co-author links

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2 shared papersBioinformatics

Martin EisenacherORCID

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2 papers

Recent·Most cited

BioinformaticsPLoS ONEPeer-reviewedOct 21, 2022

Characterization of peptide-protein relationships in protein ambiguity groups via bipartite graphs

Karin Schork, Michael Turewicz, Julian Uszkoreit…·Martin Eisenacher

This study analyzes bipartite peptide-protein graphs in proteomics, showing how graph structures vary with data type and organism, and highlights the challenge of quantifying proteins without unique peptides.

8 citations

metagenomicsproteomics

𝕏 PostBluesky

BioinformaticsbioRxivPreprintOct 18, 2021

GoMi - A new gold standard corpus for miRNA Named Entity Recognition to test dictionary, rule-based and machine-learning approaches.

Anika Frericks-Zipper, Markus Stepath, Karin Schork…·Martin Eisenacher

The paper introduces GoMi, a manually curated gold standard corpus for miRNA Named Entity Recognition, to train and test machine learning and rule-based approaches.

1 citation

machine learning (classical)benchmarking

𝕏 PostBluesky