Article ; Online: Harnessing machine learning for development of microbiome therapeutics.
2021 Volume 13, Issue 1, Page(s) 1–20
Abstract: ... a mine of information for the development of new therapeutics. Machine learning (ML), a branch ... to discover, design, and characterize microbiome therapeutics. The use of ML to optimize advanced processes ... targeted therapeutics. A background on ML will be given, followed by a guide on where to find reliable ...
Abstract | The last twenty years of seminal microbiome research has uncovered microbiota's intrinsic relationship with human health. Studies elucidating the relationship between an unbalanced microbiome and disease are currently published daily. As such, microbiome big data have become a reality that provide a mine of information for the development of new therapeutics. Machine learning (ML), a branch of artificial intelligence, offers powerful techniques for big data analysis and prediction-making, that are out of reach of human intellect alone. This review will explore how ML can be applied for the development of microbiome-targeted therapeutics. A background on ML will be given, followed by a guide on where to find reliable microbiome big data. Existing applications and opportunities will be discussed, including the use of ML to discover, design, and characterize microbiome therapeutics. The use of ML to optimize advanced processes, such as 3D printing and |
---|---|
MeSH term(s) | Artificial Intelligence ; Machine Learning ; Microbiota/physiology ; Precision Medicine |
Language | English |
Publishing date | 2021-02-02 |
Publishing country | United States |
Document type | Journal Article ; Research Support, Non-U.S. Gov't |
ZDB-ID | 2575755-6 |
ISSN | 1949-0984 ; 1949-0984 |
ISSN (online) | 1949-0984 |
ISSN | 1949-0984 |
DOI | 10.1080/19490976.2021.1872323 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
More links
Kategorien
Order via subito
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.