This paper is in the following e-collection/theme issue:

Theme Issue 2024: Machine Learning-Based Predictive Models Using Genomic Data (5) Microbial genomics and metagenomics (3) Gastroenterology and Hepatology (72) Infectious Diseases (non-STD/STI) (1592) Hygiene and Infection Prevention (325) AI applications in genomics and pathology informatics, including ‘Generative AI’ (9) Immunoinformatics and Pathology informatics (13) Machine Learning (1501) Machine Learning (55) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (39) Applications of AI (104)

Published on in Vol 5 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62747, first published .
Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach

Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach

Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach

Authors of this article:

Amy Marie Campbell1, 2 Author Orcid Image ;   Chris Hauton1 Author Orcid Image ;   Ronny van Aerle2 Author Orcid Image ;   Jaime Martinez-Urtaza2, 3 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.