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Microbial Dark Matter: from Discovery to Applications

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摘要 With the rapid increase of the microbiome samples and sequencing data,more and more knowledge about microbial communities has been gained.However,there is still much more to learn about microbial communities,including billions of novel species and genes,as well as countless spatiotemporal dynamic patterns within the microbial communities,which together form the microbial dark matter.In this work,we summarized the dark matter in microbiome research and reviewed current data mining methods,especially artificial intelligence(AI)methods,for different types of knowledge discovery from microbial dark matter.We also provided case studies on using AI methods for microbiome data mining and knowledge discovery.In summary,we view microbial dark matter not as a problem to be solved but as an opportunity for AI methods to explore,with the goal of advancing our understanding of microbial communities,as well as developing better solutions to global concerns about human health and the environment.
出处 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2022年第5期867-881,共15页 基因组蛋白质组与生物信息学报(英文版)
基金 partially supported by the National Natural Science Foundation of China(Grant Nos.32071465,31871334,and 31671374) the National Key R&D Program of China(Grant No.2018YFC0910502).
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