Author

Holger Diedam

Bayer (Germany)ORCID 0000-0002-4673-0741Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

David GnuttiD· 1 shared Erica Manesso· 1 shared Francisco de Abreu e Lima· 1 shared Lukas Hebig· 1 shared Patrick BalzerowskiiD· 1 shared Thomas Müller· 1 shared

Activity by Year

2024-2024 · peak 1/yr

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6 top collaborators · 15 mutual co-author links

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1 shared paperBioinformatics

David GnuttORCID

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1 paper

Recent·Most cited

A deep-learning based analysis framework for ultra-high throughput screening time-series data

Patrick Balzerowski, Lukas Hebig, Francisco de Abreu e Lima, Erica Manesso, Thomas Müller, Holger Diedam, David Gnutt

This paper introduces a deep-learning framework for analyzing ultra-high throughput screening time-series data, identifying two distinct classes of substances with different biological modes of action.

bioRxiv · Aug 22, 2024 · PreprintBioinformatics