Integrated Bioinformatics and Information Technology Platform for High-Throughput Sequencing in Microbial Metagenomics Based on Big Data Processing

被引:1
|
作者
Zhao, Shuo [1 ]
Zhang, Lijia [1 ]
Hu, Zhengyi [2 ]
机构
[1] Univ Chinese Acad Sci, CRE, Beijing 100049, Peoples R China
[2] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, Beijing 100085, Peoples R China
基金
中国国家自然科学基金;
关键词
Metagenomics; Big Data Technology; High-Throughput Sequencing; Bioinformatics Analysis; 16S RIBOSOMAL-RNA; AMERICAN LIGHT SMOKERS; MUSCA-DOMESTICA L; INSENSITIVE ACETYLCHOLINESTERASE; BOTULINUM NEUROTOXINS; MINE TAILINGS; HOUSE-FLY; BACTERIA; COMMUNITIES; STRAIN;
D O I
10.1166/jmihi.2018.2350
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Development of high-throughput sequencing technologies to promote the application of big data bacterial and metagenomics research is most critical, and requires a mature set of computational methods. The analysis is carried out using an integrated bioinformatics and information technology platform. Bioinformatics applied to bacterial metagenomics research plays a vital role in sequencing technologies based on big data processing. It runs through the metagenomics data collection and storage, data processing and analysis phase, which forms the biggest bottlenecks of the metagenomics process. This paper describes and summarizes commonly used techniques in high-throughput metagenomic sequencing bioinformatics analysis platform that is used for the analysis of important information. Within the next few decades, sequencing costs will decline and an increase in depth of sequencing will further increase metagenomics research in terms of data storage, data processing, and data mining complexity. Therefore, the techniques and methods pertaining to bioinformatics research are imperative. In the near future, we need to strengthen our basic analysis and storage platform to facilitate the analysis of the common bacteria, and resolve the bottlenecks of bioinformatics analysis. For this, critical breakthroughs need to be gradually developed. The methods described in this paper give a good insight into the big data technology revolving metagenomics research.
引用
收藏
页码:325 / 330
页数:6
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