Editorial: Computational Predictions, Dynamic Tracking, and Evolutionary Analysis of Antibiotic Resistance Through the Mining of Microbial Genomes and Metagenomic Data

Liang Wang; Alfred Chin Yen Tay; Jian Li; Qi Zhao

doi:10.3389/fmicb.2022.880967

Editorial: Computational Predictions, Dynamic Tracking, and Evolutionary Analysis of Antibiotic Resistance Through the Mining of Microbial Genomes and Metagenomic Data

Liang Wang
, Alfred Chin Yen Tay
, Jian Li
, Qi Zhao

Marshall Centre

Research output: Contribution to journal › Editorial › peer-review

1 Citation (Scopus)

Original language	English
Article number	880967
Journal	Frontiers in Microbiology
Volume	13
DOIs	https://doi.org/10.3389/fmicb.2022.880967
Publication status	Published - 4 Apr 2022

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10.3389/fmicb.2022.880967Licence: CC BY

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title = "Editorial: Computational Predictions, Dynamic Tracking, and Evolutionary Analysis of Antibiotic Resistance Through the Mining of Microbial Genomes and Metagenomic Data",

keywords = "antibiotic resistance, computational predictions, evolutionary analysis, metagenomic data, microbial genomes",

author = "Liang Wang and Tay, \{Alfred Chin Yen\} and Jian Li and Qi Zhao",

year = "2022",

month = apr,

day = "4",

doi = "10.3389/fmicb.2022.880967",

language = "English",

volume = "13",

journal = "Frontiers in Microbiology",

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T2 - Computational Predictions, Dynamic Tracking, and Evolutionary Analysis of Antibiotic Resistance Through the Mining of Microbial Genomes and Metagenomic Data

AU - Wang, Liang

AU - Tay, Alfred Chin Yen

AU - Li, Jian

AU - Zhao, Qi

PY - 2022/4/4

Y1 - 2022/4/4

KW - antibiotic resistance

KW - computational predictions

KW - evolutionary analysis

KW - metagenomic data

KW - microbial genomes

UR - https://www.scopus.com/pages/publications/85128472312

U2 - 10.3389/fmicb.2022.880967

DO - 10.3389/fmicb.2022.880967

M3 - Editorial

C2 - 35444627

AN - SCOPUS:85128472312

SN - 1664-302X

VL - 13

JO - Frontiers in Microbiology

JF - Frontiers in Microbiology

M1 - 880967

ER -

Editorial: Computational Predictions, Dynamic Tracking, and Evolutionary Analysis of Antibiotic Resistance Through the Mining of Microbial Genomes and Metagenomic Data

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