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Michael Imelfort

Researcher at University of Queensland

Publications -  25
Citations -  10722

Michael Imelfort is an academic researcher from University of Queensland. The author has contributed to research in topics: Genome & Population. The author has an hindex of 21, co-authored 25 publications receiving 6322 citations. Previous affiliations of Michael Imelfort include Australian Centre for Plant Functional Genomics.

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Journal ArticleDOI

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

TL;DR: An objective measure of genome quality is proposed that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities and is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches.
DatasetDOI

CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes: supplemental material

TL;DR: Refining a marker set for lineage-specific Gene Loss and Duplication Estimates under Opal Stop Codon Recodings and Mean absolute error of completeness and contamination estimates determined using different universal- and domain-specific marker gene sets.
Journal ArticleDOI

Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage

TL;DR: Metagenomic, single-cell genomic and metatranscriptomic analyses combined with bioreactor performance and 13C- and 15N-labelling experiments show that ANME-2d is capable of independent AOM through reverse methanogenesis using nitrate as the terminal electron acceptor and Comparative analyses reveal that the genes for nitrate reduction were transferred laterally from a bacterial donor, suggesting selection for this novel process within ANME -2d.
Journal ArticleDOI

Fast, accurate error-correction of amplicon pyrosequences using Acacia

TL;DR: A tool for homopolymer error-correction that has greater scalability than existing tools and a quicker but less sensitive statistical approach to distinguish between error and genuine sequence differences is developed.
Journal ArticleDOI

GroopM: an automated tool for the recovery of population genomes from related metagenomes

TL;DR: GroopM is introduced, an automated binning tool that primarily uses differential coverage to obtain high fidelity population genomes from related metagenomes and it is shown that GroopM produces results comparable with more time consuming, labor-intensive methods.