New software tools, databases, and resources in metabolomics: updates from 2020
Open accessAbstract
Background Precision medicine, space exploration, drug discovery to characterization of dark chemical space of habitats and organisms, metabolomics takes a centre stage in providing answers to diverse biological, biomedical, and environmental questions. With technological advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of analytical instrumentation. Software tools, resources, databases, and solutions help in harnessing the concealed information in the generated data for eventual translational success.Aim of the review In this review, ~ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community.Key scientific concepts of review In Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.
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Non-targeted metabolomics methods have gained significant improvement over the last decade with regards to metabolite coverage, annotation rates, and standardization of data acquisition, analysis and FAIR data sharing.
“Non-targeted metabolomics methods have gained significant improvement over the last decade with regards to metabolite coverage, annotation rates as well as standardization of data acquisition, analysis and FAIR data sharing.171,172”
From Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products (2024) · cites this paper as [172]
The Introduction (page unavailable) reports improved metabolome detection coverage and examples of data harmonization; Annotation tools (page unavailable) describes advances in compound identification. The paper does not establish a decade-long improvement in annotation rates or standardization of data acquisition, analysis, and FAIR data sharing. (LLM, conf=0.83)
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References 125 · Cited by 227
Research works printed but not linked: 1
- Kockmann, T., & Panse, C. (2020). rawR - Direct access to raw mass spectrometry data in R. bioRxiv, 2020.10.30.362533. 10.1101/2020.10.30.362533 · DOI
- Authors
- Misra, B. B.
- Corresponding author
- Misra, Biswapriya B.
- ORCID
- Misra, Biswapriya B.
- Venue
- Metabolomics
- Published
- 2021-05
- Volume
- 17
- Issue
- 5
- Pages
- 49-49
- ISSN
- 1573-3882 (ISSN-L)
- 1573-3890
- PMC
- PMC8112213
- OpenAlex
- W3162917764
- Cited by
- 227
- References
- 125
- Citations by year
- 2026: 22 · 2025: 42 · 2024: 56 · 2023: 37 · 2022: 50 · 2021: 19 · 2020: 1
- FWCI
- 4.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Metabolomics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- metabolomics databases, bioinformatics software, mass spectrometry data analysis, software resources, big data analytics
- MeSH terms
- Software, Mass Spectrometry, Databases, Factual, Proteomics, Metabolomics
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