Identification of 76 novel B1 metallo-β-lactamases through large-scale screening of genomic and metagenomic data.
about
DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.The Resistome of Low-Impacted Marine Environments Is Composed by Distant Metallo-β-Lactamases Homologs.The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants-but not always.Diversity and Proliferation of Metallo-β-Lactamases: a Clarion Call for Clinically Effective Metallo-β-Lactamase InhibitorsSystematic Identification and Classification of β-Lactamases Based on Sequence Similarity Criteria: β-Lactamase Annotation
P2860
Identification of 76 novel B1 metallo-β-lactamases through large-scale screening of genomic and metagenomic data.
description
2017 nî lūn-bûn
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2017年の論文
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2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
2017年论文
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2017年论文
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name
Identification of 76 novel B1 ...... genomic and metagenomic data.
@en
type
label
Identification of 76 novel B1 ...... genomic and metagenomic data.
@en
prefLabel
Identification of 76 novel B1 ...... genomic and metagenomic data.
@en
P2093
P2860
P50
P1433
P1476
Identification of 76 novel B1 ...... f genomic and metagenomic data
@en
P2093
Carl-Fredrik Flach
Fanny Berglund
Stathis Kotsakis
Tobias Österlund
P2860
P2888
P356
10.1186/S40168-017-0353-8
P407
P577
2017-10-12T00:00:00Z
P6179
1092156266