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Machine learning for data integration in human gut microbiome
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- Li, Peishun, 1988 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Luo, Hao, 1992 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Ji, Boyang, 1983 (author)
- Chalmers tekniska högskola,Chalmers University of Technology,BioInnovation Institute (BII)
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- (creator_code:org_t)
- 2022-11-23
- 2022
- English.
- In: Microbial Cell Factories. - : Springer Science and Business Media LLC. - 1475-2859. ; 21:1
- Research review (peer-reviewed)
Abstract
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- Recent studies have demonstrated that gut microbiota plays critical roles in various human diseases. High-throughput technology has been widely applied to characterize the microbial ecosystems, which led to an explosion of different types of molecular profiling data, such as metagenomics, metatranscriptomics and metabolomics. For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. In this review, we first discuss how dysbiosis of the intestinal microbiota is linked to human disease development and how potential modulation strategies of the gut microbial ecosystem can be used for disease treatment. In addition, we introduce categories and workflows of different machine learning approaches, and how they can be used to perform integrative analysis of multi-omics data. Finally, we review advances of machine learning in gut microbiome applications and discuss related challenges. Based on this we conclude that machine learning is very well suited for analysis of gut microbiome and that these approaches can be useful for development of gut microbe-targeted therapies, which ultimately can help in achieving personalized and precision medicine.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
Keyword
- Precision medicine
- Multi-omics
- Gut microbiome
- Machine learning
- Data integration
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