Author

Tomasz Grzegorzek

Nvidia (United States)ORCID 0000-0002-9720-4901Unclaimed 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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Research Focus:drug response / drug discovery· 1 Assay:proteomics· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Damian NeubaueriD· 1 shared Ewa SzczurekiD· 1 shared Jacek SrokaiD· 1 shared Karol SikoraiD· 1 shared Marcin MożejkoiD· 1 shared Marta BaueriD· 1 shared Michał MichalskiiD· 1 shared Paulina SzymczakiD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Damian NeubauerORCID

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1 paper

Recent·Most cited

Discovering highly potent antimicrobial peptides with deep generative model HydrAMP

Paulina Szymczak, Marcin Możejko, Tomasz Grzegorzek, Radosław Jurczak, Marta Bauer, Damian Neubauer, Karol Sikora, Michał Michalski, Jacek Sroka, Piotr Setny, Wojciech Kamysz, Ewa Szczurek

This paper introduces HydrAMP, a deep generative model for creating potent antimicrobial peptides, which outperforms existing methods and validates nine new peptides in lab tests.

Nature Communications · Mar 15, 2023Peer-reviewedBioinformatics