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本文引用的文献

1
VADR: validation and annotation of virus sequence submissions to GenBank.VADR:病毒序列提交到 GenBank 的验证和注释。
BMC Bioinformatics. 2020 May 24;21(1):211. doi: 10.1186/s12859-020-3537-3.
2
GeneMark-EP+: eukaryotic gene prediction with self-training in the space of genes and proteins.GeneMark-EP+:在基因和蛋白质空间中进行自我训练的真核基因预测
NAR Genom Bioinform. 2020 Jun;2(2):lqaa026. doi: 10.1093/nargab/lqaa026. Epub 2020 May 13.
3
ASA3P: An automatic and scalable pipeline for the assembly, annotation and higher-level analysis of closely related bacterial isolates.ASA3P:一个用于组装、注释和高级分析密切相关的细菌分离物的自动且可扩展的流水线。
PLoS Comput Biol. 2020 Mar 5;16(3):e1007134. doi: 10.1371/journal.pcbi.1007134. eCollection 2020 Mar.
4
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens.CAFA 挑战赛报告称,通过实验筛选,提高了数百个基因的蛋白质功能预测和新的功能注释。
Genome Biol. 2019 Nov 19;20(1):244. doi: 10.1186/s13059-019-1835-8.
5
DeepGOPlus: improved protein function prediction from sequence.DeepGOPlus:从序列中改进蛋白质功能预测。
Bioinformatics. 2020 Jan 15;36(2):422-429. doi: 10.1093/bioinformatics/btz595.
6
GAAP: A Genome Assembly + Annotation Pipeline.GAAP:基因组组装与注释流水线。
Biomed Res Int. 2019 Jun 26;2019:4767354. doi: 10.1155/2019/4767354. eCollection 2019.
7
Environmental conditions shape the nature of a minimal bacterial genome.环境条件决定了最小细菌基因组的性质。
Nat Commun. 2019 Jul 15;10(1):3100. doi: 10.1038/s41467-019-10837-2.
8
Next-generation genome annotation: we still struggle to get it right.下一代基因组注释:我们仍在努力做到正确。
Genome Biol. 2019 May 16;20(1):92. doi: 10.1186/s13059-019-1715-2.
9
Whole-Genome Annotation with BRAKER.使用BRAKER进行全基因组注释。
Methods Mol Biol. 2019;1962:65-95. doi: 10.1007/978-1-4939-9173-0_5.
10
Structural and Functional Annotation of Eukaryotic Genomes with GenSAS.使用GenSAS对真核生物基因组进行结构和功能注释。
Methods Mol Biol. 2019;1962:29-51. doi: 10.1007/978-1-4939-9173-0_3.

疾病微生物的基因组注释。

Genome annotation of disease-causing microorganisms.

机构信息

College of Public Health, University of South Florida, Tampa, FL, USA.

Division of Infectious Disease and International Medicine, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.

出版信息

Brief Bioinform. 2021 Mar 22;22(2):845-854. doi: 10.1093/bib/bbab004.

DOI:10.1093/bib/bbab004
PMID:33537706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7986607/
Abstract

Humans have coexisted with pathogenic microorganisms throughout its history of evolution. We have never halted the exploration of pathogenic microorganisms. With the improvement of genome-sequencing technology and the continuous reduction of sequencing costs, an increasing number of complete genome sequences of pathogenic microorganisms have become available. Genome annotation of this massive sequence information has become a daunting task in biological research. This paper summarizes the approaches to the genome annotation of pathogenic microorganisms and the available popular genome annotation tools for prokaryotes, eukaryotes and viruses. Furthermore, real-world comparisons of different annotation tools using 12 genomes from prokaryotes, eukaryotes and viruses were conducted. Current challenges and problems were also discussed.

摘要

人类在其进化历史上一直与致病微生物共存。我们从未停止过对致病微生物的探索。随着基因组测序技术的提高和测序成本的不断降低,越来越多的致病微生物完整基因组序列得以问世。对这些海量序列信息进行基因组注释已成为生物研究中的一项艰巨任务。本文总结了致病微生物基因组注释的方法以及现有的用于原核生物、真核生物和病毒的流行基因组注释工具。此外,还使用来自原核生物、真核生物和病毒的 12 个基因组对不同注释工具进行了实际比较。同时还讨论了当前面临的挑战和问题。