Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences
He graduated from the University of Chinese Academy of Sciences in 2014 with a Ph.D. in bioinformatics, and then worked in the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences as a postdoctoral fellow, engineer, and senior engineer, and joined the Shenzhen Institute of Agricultural Genomics, Chinese Academy of Agricultural Sciences in October 2022 as a research team leader. His research interests include metagenomic approaches, food microbiome, and science communication. Participated in the QIIME 2 project, led the development of easyAmplicon, EasyMetagenome, culturome analysis pipelines, data analysis websites (EVenn, ImageGP) and R packages (amplicon, ggClusterNet), etc., with the goal of comprehensively building the methodological infrastructure in the field of metagenomics and promoting the development of microbiome. He has published more than 20 papers in journals such as Nature Biotechnology, Nature Microbiology, and iMeta as the (co-)first or corresponding author. He has published more than 20 papers in journals such as Science, Cell Host & Microbe, and Microbiome, with a total of more than 40 papers and 10,000+ citations. He edited the monograph "Microbiome Experiment Manual", with the participation of more than 300 peers, to create a long-term updated Chinese encyclopedia in this field. Founded the metagenomics public account, which has been followed by 140,000+ peers, shared more than 3,000 original articles, and has accumulated more than 30 million readers, creating the most influential science communication platform in this field. Launched the journal "iMeta", and joined hands with thousands of experts around the world to create a top journal of metagenomics, microbiome and bioinformatics to solve the problem of journal publishing in this field in China.
[1]Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
Nature biotechnology 37 (8), 852-857
[2]QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science
[3]NRT1.1B is associated with root microbiota composition and nitrogen use in field-grown rice
[4]A specialized metabolic network selectively modulates Arabidopsis root microbiota
[5]A practical guide to amplicon and metagenomic analysis of microbiome data
[6]Expression of the nitrate transporter gene OsNRT1. 1A/OsNPF6. 3 confers high yield and early maturation in rice
[7]Root microbiota shift in rice correlates with resident time in the field and developmental stage
[8]ImageGP: An easy‐to‐use data visualization web server for scientific researchers
[9]EVenn: Easy to create repeatable and editable Venn diagrams and Venn networks online
[10]Reductionist synthetic community approaches in root microbiome research