Article

Nanopore- and AI-empowered microbial viability inference

2024-06-11

Abstract excerpt

The ability to differentiate between viable and dead microorganisms in metagenomic data is crucial for various microbial inferences, ranging from assessing ecosystem functions of environmental microbiomes to inferring the virulence of potential pathogens from metagenomic analysis. While established viability-resolved genomic approaches are labor-intensive as well as biased and lacking in sensitivity, we here intro...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 26e30f8f-d7ed-54f7-bd2d-ee4f6d30f529
DOI: 10.1101/2024.06.10.598221

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 10 closest

Nanopore- and AI-empowered microbial viability inferenceDOI 10.1101/2024.06.10.598221Read

Whole microbial community viability is not quantitatively reflected by propidium monoazide sequencing approachSemantic proximity Read

Label-free Pathogen Identification with Microscopy Imaging and Deep LearningSemantic proximity Read

Living Bacterial Reservoir Computers for Information Processing and SensingSemantic proximity Read

Real-Time, Direct Classification of Nanopore Signals with SquiggleNetSemantic proximity Read

Strain Level Microbial Detection and Quantification with Applications to Single Cell MetagenomicsSemantic proximity Read

Beyond culturability: VBNC-like and differentially culturable Mycobacterium tuberculosis challenge growth-based interpretations of bacterial viability.Semantic proximity Read

Review ofChlamydia trachomatisviability methods: assessing the clinical diagnostic impact of NAAT positive resultsSemantic proximity Read

DeePaC: Predicting pathogenic potential of novel DNA with a universal framework for reverse-complement neural networksSemantic proximity Read

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.Semantic proximity Read

AI-assisted automated endpoint interpretation for turbidity-based digital LAMP using bright-field microscopySemantic proximity Read