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Generative models for antimicrobial peptide design: auto-encoders and beyond.

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Bibliographic Details
Title:	Generative models for antimicrobial peptide design: auto-encoders and beyond.
Authors:	Beierle L; Bioinformatics and Systems Biology, Justus-Liebig-University Giessen, Ludwigsplatz, Giessen, Hesse, 35390, Germany. lukas.beierle@computational.bio.uni-giessen.de., Hahnfeld J; Bioinformatics and Systems Biology, Justus-Liebig-University Giessen, Ludwigsplatz, Giessen, Hesse, 35390, Germany., Goesmann A; Bioinformatics and Systems Biology, Justus-Liebig-University Giessen, Ludwigsplatz, Giessen, Hesse, 35390, Germany., Mostolizadeh R; Bioinformatics and Systems Biology, Justus-Liebig-University Giessen, Ludwigsplatz, Giessen, Hesse, 35390, Germany.; Max-Planck-Institute for Terrestrial Microbiology, Marburg, Hesse, 35043, Germany., Cemič F; Department of Computer Science, University of Applied Sciences Giessen, Gutfleischstrasse, Giessen, Hesse, 35390, Germany.
Source:	BioData mining [BioData Min] 2026 May 09; Vol. 19 (1). Date of Electronic Publication: 2026 May 09.
Publication Type:	Journal Article
Journal Info:	Publisher: BioMed Central Country of Publication: England NLM ID: 101319161 Publication Model: Electronic Cited Medium: Print ISSN: 1756-0381 (Print) Linking ISSN: 17560381 NLM ISO Abbreviation: BioData Min Subsets: PubMed not MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1756-0381
DOI:	10.1186/s13040-026-00558-w