A supervised statistical learning approach for accurate Legionella pneumophila source attribution during outbreaks.

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A supervised statistical learning approach for accurate Legionella pneumophila source attribution during outbreaks.

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2017 nî lūn-bûn

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2017年の論文

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2017年学术文章

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A supervised statistical learn ...... attribution during outbreaks.

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A supervised statistical learn ...... attribution during outbreaks.

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A supervised statistical learn ...... attribution during outbreaks.

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P1476

A Supervised Statistical Learn ...... e Attribution during Outbreaks

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Anders Gonçalves Da Silva

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Kyra Y L Chua

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Lucinda Franklin

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Nela Subasinghe

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Stuart Adcock

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Susan Ballard

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Takehiro Tomita

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Wei Gao

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Zoe Cutcher

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P2860

Evidence in the Legionella pneumophila genome for exploitation of host cell functions and high genome plasticity

Combined Analysis of Variation in Core, Accessory and Regulatory Genome Regions Provides a Super-Resolution View into the Evolution of Bacterial Populations

GenGIS 2: geospatial analysis of traditional and genetic biodiversity, with new gradient algorithms and an extensible plugin framework.

A pilot study of rapid whole-genome sequencing for the investigation of a Legionella outbreak

FastTree 2--approximately maximum-likelihood trees for large alignments

Prokka: rapid prokaryotic genome annotation

Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines.

Legionella pneumophila pangenome reveals strain-specific virulence factors.

Seeding and Establishment of Legionella pneumophila in Hospitals: Implications for Genomic Investigations of Nosocomial Legionnaires' Disease.

Genomic investigation of a suspected outbreak of Legionella pneumophila ST82 reveals undetected heterogeneity by the present gold-standard methods, Denmark, July to November 2014

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scholarly article

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10.1128/AEM.01482-17

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English

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P478

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P577

2017-10-17T00:00:00Z

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28821546

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5648911

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