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Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite ...
The first book on metabolomics was published in 2003. [5] The first journal dedicated to metabolomics (titled simply "Metabolomics") was launched in 2005 and is currently edited by Prof. Roy Goodacre. Some of the more significant early papers on metabolome analysis are listed in the references below. [6] [7] [8] [9]
Metabolomics: Study of metabolism and the function and interactions of metabolic breakdown products, or metabolites. 4. Transcriptomics: Study of the full complement of RNA in an organism's cells.
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances.KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.
Metabolic engineering is the practice of optimizing genetic and regulatory processes within cells to increase the cell's production of a certain substance. These processes are chemical networks that use a series of biochemical reactions and enzymes that allow cells to convert raw materials into molecules necessary for the cell's survival.
Number of citations of the terms "Multiomics" and "Multi-omics" in PubMed until the 31st December 2021. Multiomics, multi-omics, integrative omics, "panomics" or "pan-omics" is a biological analysis approach in which the data sets are multiple "omes", such as the genome, proteome, transcriptome, epigenome, metabolome, and microbiome (i.e., a meta-genome and/or meta-transcriptome, depending ...
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Metabolite Set Enrichment Analysis (MSEA) is a method designed to help metabolomics researchers identify and interpret patterns of metabolite concentration changes in a biologically meaningful way. [1] It is conceptually similar to another widely used tool developed for transcriptomics called Gene Set Enrichment Analysis or GSEA. [2]