Results 101 to 110 of about 1,283,302 (227)

metagenome-atlas/atlas: Large gene catalogs

open access: yes, 2022
What's Changed Make atlas handle large gene catalogs using parquet and pyfastx parquet files can be opened in python with import pandas as pd coverage = pd.read_parquet("working_dir/Genecatalog/counts/median_coverage.parquet") coverage.set_index ...
Silas Kieser   +15 more
core   +1 more source

Hybrid Clustering of Long and Short-read for Improved Metagenome Assembly [PDF]

open access: yes, 2021
Next-generation sequencing has enabled metagenomics, the study of the genomes of microorganisms sampled directly from the environment without cultivation.
Mascagni, Michael   +6 more
core   +1 more source

A Metagenome‐Assembled Genome Catalog From the Global Ruminant Microbiomes

open access: yesAnimal Research and One Health, EarlyView.
The Ruminant Gastrointestinal MAG Catalog (RGMC) is a comprehensive global resource offering 40,812 strain‐level genomes across 53 bacterial and 4 archaeal classes. It greatly surpasses prior efforts in scale and diversity, serving as an essential foundation for research in ruminant nutrition, microbial function, and methane mitigation.
Shizhe Zhang   +8 more
wiley   +1 more source

Metagenome-assembled genomes (MAGs)

open access: yes
The MetaWRAP pipeline was employed for genome assembly and binning. Specifically, MEGAHIT was used to assemble sequences and generate contigs. Prodigal was used to predict open reading frames (ORFs) in each contig.
Zhou (18148486)
core   +1 more source

Assemble CRISPRs from metagenomic sequencing data [PDF]

open access: yesBioinformatics, 2016
Abstract Motivation Clustered regularly interspaced short palindromic repeats and associated proteins (CRISPR-Cas) allows more specific and efficient gene editing than all previous genetic engineering systems.
Jikai Lei, Yanni Sun
openaire   +2 more sources

ExMODE: A comprehensive resource for extremophile genomic and functional exploration

open access: yesiMetaOmics, EarlyView.
ExMODE (https://db.genomics.cn/exmode/) integrates 3518 samples to build a unified extremophile resource, which hosts 1.35 billion habitat‐specific non‐redundant genes, 5.25 million representative protein structures, 67,026 metagenome‐assembled genomes (MAGs), and 164,132 biosynthetic gene clusters (BGCs). By combining sequence‐, structure‐, and genome‐
Denghui Li   +30 more
wiley   +1 more source

Multi‐omics reveals gastrointestinal metabolic disorder‐induced diarrhea in postpartum dairy cows

open access: yesiMetaOmics, EarlyView.
Nutritional diarrhea is a pervasive, costly challenge in dairy production. Using integrated metagenomic and metabolomic profiling, we identified coordinated microbial and metabolic alterations across the rumen, hindgut, and serum. In the rumen, enrichment of Prevotella sp.
Weixuan Tang   +7 more
wiley   +1 more source

Evaluating and improving the representation of bacterial contents in long-read metagenome assemblies

open access: yesGenome Biology
Background In the metagenomic assembly of a microbial community, abundant species are often thought to assemble well given their deeper sequencing coverage. This conjuncture is rarely tested or evaluated in practice.
Xiaowen Feng, Heng Li
doaj   +1 more source

Metagenomic and culture‐based insights into host and plasmid contexts of high‐risk ARGs in poultry farm environments

open access: yesiMetaOmics, EarlyView.
Shotgun metagenomics and culture‐based isolate genomics revealed position‐associated high‐risk antibiotic resistance genes (ARGs) signals across poultry manure piles and surrounding soils. Culture‐confirmed Enterobacteriaceae and IncHI2A‐related blaNDM‐5 plasmid backgrounds further highlight priority host‐ARG‐plasmid contexts for farm antimicrobial ...
Yaling Wang   +5 more
wiley   +1 more source

A review of methods and databases for metagenomic classification and assembly [PDF]

open access: yesBriefings in Bioinformatics, 2017
Abstract Microbiome research has grown rapidly over the past decade, with a proliferation of new methods that seek to make sense of large, complex data sets. Here, we survey two of the primary types of methods for analyzing microbiome data: read classification and metagenomic assembly, and we review some of the challenges facing these
Florian P. Breitwieser   +2 more
openaire   +2 more sources

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