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Metabolomics Resources: An Introduction of Databases and Their Future Prospective

Abstract

Metabolomics, an extended branch deals with targeted metabolite analysis, takes transcriptome and proteome analysis in consideration to solve complex biological puzzles. Improved insight in the metabolomics has generated huge complex of data that makes room for improved in silico methodologies to reveal the basic biological mechanism from the generated datasets. Despite, the recently developed tools, various software and metabolomics resources available and other information in the form of databases are currently lacking in providing precise and required information. Therefore, this chapter will provide the readers an overview of available open-source tools, algorithms, and workflow strategy to familiarize, promote, and facilitate metabolomics research and data processing frameworks. Though most of the tools and resources that have been described in this chapter include data processing, data annotation, and data visualization in mass spectrometry (MS) and NMR-based metabolomics and specific tools for untargeted metabolomics workflows, few advanced tools will also be discussed. The tools and resources discussed here have well-known collaborations of analytical data with reliance in computational platform. In the end, we have discussed about the future prospective for metabolomics resources.

Keywords

  • Metabolomics
  • Databases
  • Mass spectrophotometer
  • Annotation
  • Molecular networking

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Abbreviations

API:

Application programming interfaces

CFM:

Competitive fragmentation modeling

GC-MS:

Gas chromatography-mass spectroscopy

KEGG:

Kyoto Encyclopedia of Genes and Genomes

LC-MS:

Liquid chromatography-mass chromatography

MALDI:

Matrix-free laser desorption/ionization

NMR:

Nuclear magnetic resonance

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Correspondence to Vishal Acharya .

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Kumar, N., Acharya, V. (2018). Metabolomics Resources: An Introduction of Databases and Their Future Prospective. In: Yadav, S., Kumar, V., Singh, S. (eds) Recent Trends and Techniques in Plant Metabolic Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-2251-8_7

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