ARTIFICIAL INTELLIGENCE IN METABOLOMIC RESEARCH

The term "metabolomics" refers to high-throughput methods for detecting various metabolites and small molecules in biological samples. Undirected metabolomics, also known as unbiased global metabolome analysis, can be used discover key variables or measurements of human health illness. From this vantage point, it is investigated how artificial intelligence machine learning enable significant advances non-targeted metabolic processes well findings the early detection diagnosis diseases (Jung-Ming G. Lin, et al. 2022). Metabolomics important finding cures many diseases. In development innovations field biotechnology, great importance collect, filter, analyze, use information smart data. For reason, biotechnology companies healthcare organizations around world have created large databases. This data accelerates products areas. Algorithms are being developed analysis. It thought that disease treatments will found when genome edited. Machine techniques effective tools metabolomic investigation; however, they only straightforward computing scenarios. When functionally, formatting frequently calls sub-computational resources not covered area.