Microbial Dark Matter:from Discovery to Applications
- Author:
Zha YUGUO
1
;
Chong HUI
;
Yang PENGSHUO
;
Ning KANG
Author Information
1. MOE Key Laboratory of Molecular Biophysics,Hubei Key Laboratory of Bioinformatics and Molecular-imaging,Center of Artificial Intelligence Biology,Department of Bioinformatics and Systems Biology,College of Life Science and Technology,Huazhong University of Science and Technology,Wuhan 430074,China
- Keywords:
Microbiome;
Dark matter;
Artificial intelligence;
Knowledge discovery;
Application
- From:
Genomics, Proteomics & Bioinformatics
2022;20(5):867-881
- CountryChina
- Language:Chinese
-
Abstract:
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 count-less 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 solu-tions to global concerns about human health and the environment.
