Author

Martin Held

ETH ZurichORCID 0000-0002-5952-5659Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Microbiology· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:protein sequence· 1

Frequent Co-Authors

Sven PankeiD· 2 shared Andreas Meyer· 1 shared Jan Maarten van DijliD· 1 shared Liz Armas‐EgasiD· 1 shared Margriet M. W. B. HendriksiD· 1 shared Priscilla ZwartjensiD· 1 shared René Pellaux· 1 shared Sandra Lagler· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersMicrobiology

Sven PankeORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

MicrobiologybioRxivPreprintAug 6, 2026

Chimerophore antibiotics: engineered multimodal host defense peptides

Liz Armas‐Egas, Sandra Lagler, Sven Panke, Martin Held

The paper designs chimerophore antibiotics by fusing non-lytic HDPs to create multimodal peptides with broad-spectrum activity and serum tolerance.

DOI 10.64898/2026.08.06.743220

experimental assaydrug response / drug discovery

𝕏 PostBluesky

Synthetic BiologyACS Synthetic BiologyPeer-reviewedJan 17, 2023

Signal peptide efficiency: from high-throughput data to prediction and explanation

Stefano Grasso, Valentina Dabene, Margriet M. W. B. Hendriks…·Tjeerd van Rij

The paper evaluates 12,000 signal peptides using a high-throughput assay, trains a machine learning model to predict secretion efficiency, and explains the model's features.

57 citationstop 3%

protein sequencemachine learning (classical)

𝕏 PostBluesky