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解决基因组难题:宏基因组 binning 的计算方法。

Solving genomic puzzles: computational methods for metagenomic binning.

机构信息

Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia.

Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia.

出版信息

Brief Bioinform. 2024 Jul 25;25(5). doi: 10.1093/bib/bbae372.

Abstract

Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.

摘要

宏基因组学涉及直接从生活在自然环境中的微生物群落中获取的遗传物质的研究。宏基因组学领域为微生物群落的结构、多样性和生态学提供了有价值的见解。一旦对环境样本进行测序和处理,宏基因组分类就会将序列聚类到代表不同分类群(如物种、属或更高水平)的分类中。已经开发了几种计算工具来自动执行宏基因组分类过程。这些工具使我们能够恢复微生物的新草案基因组,从而研究它们在微生物群落中的行为和功能。本综述对不同的宏基因组分类方法以及这些方法使用的不同细化、可视化和评估技术进行了分类和分析。此外,该综述还强调了该研究领域当前存在的挑战和改进领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/babe/11289683/2fba05d1f440/bbae372f1.jpg

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