Microbiome search engine: microbiome search and data mining
Last Update: 2020-06-20
Search more information of high quality chemicals, good prices and reliable suppliers, visit
Microbiome is the form of microbial presence in nature, which is closely related to the health of human body, air, soil and oceanTherefore, microbiome science and industry has become the "strategic highland" of international scientific and technological cooperation and competitionHowever, the lack of big data mining tools hinders the leap of microbiome research from "data analysis" to "data science"In 2010, more than 500 researchers from 43 countries jointly launched the Earth Microbiome ProjectEMP), a systematic survey of the diversity of the global microbiome, has published the results of the first phase (Thompson, et al., Nature, 2017)The Human Microbiome Project, which governments have been launching over the years, has been launchedHMP and the National Microbiome Initiative; NMI) and so on, also produce a large amount of microbiome dataThese metagenomes represent a variety of data types, diverse sources, large volumes, and their numbers are growing exponentiallyHowever, the lack of big data mining tools, resulting in new data is difficult to quickly compare with the original massive data, for the entire microbiome data space of the global understanding is impossible to talk aboutin response to this core scientific bottleneck, the Microbiome Search Engine was developed by the Microbiome Search Engine, a single-cell center bioinformatics research group led by Su Xiaoquan, an associate researcher at the Qingdao Institute of Bioenergy and Process studies of the Chinese Academy of SciencesMSE; ), large-scale "community-to-community" microbiome search and data miningMSE achieves a rapid comparison based on the structure or functional similarity of the floraIn the million-sample scale database, two similarities between all microgroups are calculated to reconstruct the global microbiome data space image, with traditional algorithms taking 230 days, compared with HALF a day for MSEIn turn, the target flora is precisely located in the global data space, with the traditional algorithm taking 100 seconds, while the MSE takes only 0.29 secondsAs a result, MSE makes large-scale, global microbial group comparison and search possible for the first timebenefitfrom MSE's powerful microbiome structure-to-search capabilities, and researchers based on microbiome big data, the researchers proposed a Microbiome Focus Index for objectivequanizing the "novelty" and "concern" of the floraMFI) " By continuously tracking trends in MFI between 2010 and 2017, researchers unearthed 2,238 "Sleeping Beauty" samples from a microbial group of more than 100,000 cases: those that were originally originally structured but lacklustre, but that will receive great research attention within four years of publication Such samples are found mainly in the oceans (51%), indoor homes (20%), mammalian intestines (19%), and mother-to-child transmission (1%) Research on such samples often has far-reaching scientific implications, but the current level of research attention and investment is far from sufficient Therefore, MFI reveals the global characteristics of the current microbiome structural space and predicts the data and areas with the greatest scientific potential and investment value This big data analysis platform can provide reference for the design and implementation of microbiome programs, and also help to think about the current situation and trends of microbiome development published in the journal mBio MSE is the first big data mining tool developed by Chinese researchers in the Earth Microbiology Group program It will serve the research group of microbiome at home and abroad as one of the core computing platforms of EMP, and support the implementation of the Microbiome Plan of the Chinese Academy of Sciences Su Xiaoquan, a researcher, and Rob Knight, a professor at the University of California, San Diego, co-author of the paper, are co-authors of the single-cell center, Xu Jian, and EMP founder The project has been supported by the Microbiology Group Program of the Chinese Academy of Sciences, the major basic research projects of the Natural Science Foundation of Shandong Province, and the National Natural Science Foundation of China paper information: Su X, Jing G, McDonald D, Wang H, Wang Z, Gonzalez A, Sun Z, Huang S, Navas J, Knight R., Xu J (2018) Identifying and predicting novelty in microbiome studies mBio doi: 10.1128/mBio.02099-18. Source: , Qingdao Institute of Bioenergy and Process
This article is an English version of an article which is originally in the Chinese language on echemi.com and is provided for information purposes only.
This website makes no representation or warranty of any kind, either expressed or implied, as to the accuracy, completeness ownership or reliability of
the article or any translations thereof. If you have any concerns or complaints relating to the article, please send an email, providing a detailed
description of the concern or complaint, to email@example.com
. A staff member will contact you within 5 working days. Once verified, infringing content
will be removed immediately.