Digital phagograms: predicting phage infectivity through a multilayer machine learning approach-Reference-Cited by-同舟云学术

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Digital phagograms: predicting phage infectivity through a multilayer machine learning approach

Published:2022-02 Issue: Volume:52 Page:174-181
ISSN:1879-6257
Container-title:Current Opinion in Virology
language:en
Short-container-title:Current Opinion in Virology

Author:

Lood Cédric^ORCID,Boeckaerts Dimitri,Stock Michiel^ORCID,De Baets Bernard^ORCID,Lavigne Rob,van Noort Vera^ORCID,Briers Yves^ORCID

Publisher

Elsevier BV

Subject

Virology

Reference62 articles.

1. Bacteria-phage coevolution as a driver of ecological and evolutionary processes in microbial communities;Koskella;FEMS Microbiol Rev,2014

2. Prophage genomics;Canchaya;Microbiol Mol Biol Rev,2003

3. Importance of prophages to evolution and virulence of bacterial pathogens;Fortier;Virulence,2013

4. Bacteriophages as drivers of bacterial virulence and their potential for biotechnological exploitation;Schroven;FEMS Microbiol Rev,2021

5. The future of bacteriophage biology;Campbell;Nat Rev Genet,2003

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3. Unlocking data inKlebsiellalysogens to predict capsular type-specificity of phage depolymerases;2024-07-25

4. Link Prediction in Stagewise Graphs;IEEE Transactions on Knowledge and Data Engineering;2024-07

5. Prediction of Klebsiella phage-host specificity at the strain level;Nature Communications;2024-05-22

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