Author

Gerrit Großmann

German Research Centre for Artificial IntelligenceORCID 0000-0002-4933-447XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

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Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexey A. GurevichiD· 1 shared Azat TagirdzhanoviD· 1 shared Daria Pavliuk· 1 shared David SelbyiD· 1 shared F. P. Jake HaeckliD· 1 shared Hind RakiiD· 1 shared Jan EwaldiD· 1 shared Kevin George· 1 shared

Activity by Year

2024-2025 · peak 1/yr

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10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Alexey A. GurevichORCID

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2 papers

Recent·Most cited

BioinformaticsFrontiers in Artificial IntelligencePeer-reviewedJul 17, 2025

Visible neural networks for multi-omics integration: a critical review

David Selby, Rashika Jakhmola, Maximilian Sprang…·Sebastian J. Vollmer

This paper reviews 86 studies on biologically informed neural networks for multi-omics integration, highlighting trends and challenges in terminology, tools, and evaluation methods.

19 citations

benchmark studybenchmarking

BioinformaticsbioRxivPreprintNov 11, 2024

GRIP: physics-informed neural network for gradient retention time prediction in liquid chromatography

Kevin George, F. P. Jake Haeckl, Gerrit Großmann…·Azat Tagirdzhanov

GRIP predicts gradient retention times using physics-informed neural networks, showing zero-shot generalization and performance comparable to transfer learning baselines.

DOI 10.1101/2024.11.11.622855

deep learningstatistical model