Improved metagenome binning and assembly using deep variational autoencoders

Despite recent advances in metagenomic binning, reconstruction of microbial species from metagenomics data remains challenging. Here we develop variational autoencoders for metagenomic binning (VAMB), a program that uses deep variational autoencoders to encode sequence coabundance and k -mer distrib...

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Vydané v:	Nature biotechnology Ročník 39; číslo 5; s. 555 - 560
Hlavní autori:	Nissen, Jakob Nybo, Johansen, Joachim, Allesøe, Rosa Lundbye, Sønderby, Casper Kaae, Armenteros, Jose Juan Almagro, Grønbech, Christopher Heje, Jensen, Lars Juhl, Nielsen, Henrik Bjørn, Petersen, Thomas Nordahl, Winther, Ole, Rasmussen, Simon
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Nature Publishing Group US 01.05.2021 Nature Publishing Group
Predmet:	631/114/2785 631/326/2565/2134 631/61/212/2142 Agriculture Bacteroides - genetics Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Clustering Datasets Deep learning Distribution patterns Electronic data processing Genetic research Genome, Bacterial - genetics Genomes Geographical distribution Humans Intestinal microflora Letter Life Sciences Machine learning Metagenome - genetics Metagenomics Methods Microbiomes Microbiota - genetics Microorganisms Molecular Sequence Annotation Nucleotides Software Technology application Denmark
ISSN:	1087-0156, 1546-1696, 1546-1696
On-line prístup:	Získať plný text
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