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- W4387172024 abstract "Clinical metabolomics may be used for the discovery of novel disease biomarkers, the diagnosis of known diseases, and the understanding or rationalization of disease mechanisms. This chapter introduces readers to some of the bioinformatic tools that can be used to facilitate clinical metabolomics and provide key insights into disease processes. In particular, readers will be introduced to several important bioinformatic tools and resources in clinical metabolomics that are widely used for metabolite identification, for biomarker discovery, for disease diagnosis, and for understanding disease mechanisms. These will include discussions on the Metabolomics Standards Initiative (MSI), software tools for metabolite identification and quantification (such as Bayesil and XCMS), data resources for metabolite annotation such as the Human Metabolome Database (HMDB) and MarkerDB (a biomarker database), data analysis and biomarker discovery tools such as MetaboAnalyst, and resources for interpreting or characterizing disease mechanisms, such as the Small Molecule Pathway Database (SMPDB). Using these and other well-known bioinformatic resources, clinicians are now able to make more precise diagnoses, integrate multiple types of omics data, and provide the framework for making metabolomics and integral part of precision medicine." @default.
- W4387172024 created "2023-09-30" @default.
- W4387172024 creator A5003573061 @default.
- W4387172024 date "2023-01-01" @default.
- W4387172024 modified "2023-09-30" @default.
- W4387172024 title "Bioinformatic Tools for Clinical Metabolomics" @default.
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- W4387172024 doi "https://doi.org/10.1007/978-981-99-5162-8_4" @default.
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