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Persistent Identifier
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perma:LIST.UAXFWP |
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Publication Date
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2026-07-06 |
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Title
| PathoFact 2.0: an integrative pipeline for the prediction of antimicrobial resistance genes, virulence factors, toxins and toxin-associated proteins, and biosynthetic gene clusters in metagenomes [* Cross-Reference *] |
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Other Identifier
| https://doi.org/10.1093/gigascience/giag062
OpenAlex ID: https://openalex.org/W7162066713 |
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Author
| Luis F Delgado (University of Luxembourg)University of LuxembourgORCIDhttps://orcid.org/0000-0001-7850-5285
Júlia Ortís Sunyer (University of Luxembourg)University of LuxembourgORCIDhttps://orcid.org/0000-0002-2714-7067
Cedric C Laczny (University of Luxembourg)University of LuxembourgORCIDhttps://orcid.org/0000-0002-1100-1282
Oskar Hickl (University of Luxembourg)University of LuxembourgORCIDhttps://orcid.org/0000-0001-9959-8767
Patrick May (University of Luxembourg)University of LuxembourgORCIDhttps://orcid.org/0000-0001-8698-3770
Paul Wilmes (University of Luxembourg, Luxembourg Institute of Science and Technology)University of Luxembourg, Luxembourg Institute of Science and TechnologyORCIDhttps://orcid.org/0000-0002-6478-2924 |
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Point of Contact
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Use email button above to contact.
LIST QDKM (LIST) |
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Description
| Background: Antimicrobial resistance genes (ARGs) and virulence factors (VFs) are central contributors to the global health crisis surrounding drug-resistant infections. Findings: We introduce PathoFact 2.0, an enhanced pipeline for improved ARG, VF, toxin, and biosynthetic gene clusters (BGCs) prediction. Key improvements include an updated machine learning (ML) model for VF identification, expanded hidden Markov model profiles for VFs and toxin-associated proteins, a new ML model for toxin and toxin-associated proteins identification, and the integration of antiSMASH 7.0 for predicting BGCs. Conclusions: Our upgrades make PathoFact 2.0 a more powerful and user-friendly platform for predicting microbiome-based pathogenicity and resistance, providing a crucial tool for better understanding and addressing the challenges posed by antimicrobial resistance and infectious diseases. PathoFact 2.0 is available at https://gitlab.com/uniluxembourg/lcsb/systems-ecology/pathofact2. It is compatible with Linux operating systems. (2026-01-01)
***This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.1093/gigascience/giag062 for the original and latest version of the publication*** (2026-07-01) |
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Subject
| Chemistry; Computer and Information Science; Medicine, Health and Life Sciences; Physics |
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Keyword
| Pipeline (software)
Virulence
Gene
Antibiotic resistance
Pathogenicity
Key (lock)
Antimicrobial
Gene cluster |
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Topic Classification
| Antibiotic Resistance in Bacteria
Machine Learning in Bioinformatics
Computational Drug Discovery Methods |
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Deposit Date
| 2026-01-01 |
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Data Type
| Article |
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Data Source
| GigaScience |