The DOI matches its Crossref record; 109 of the 109 references it cites were found in a registry or an index.
Metabolomics technology and bioinformatics
Abstract
Metabolomics is the global analysis of all or a large number of cellular metabolites. Like other functional genomics research, metabolomics generates large amounts of data. Handling, processing and analysis of this data is a clear challenge and requires specialized mathematical, statistical and bioinformatics tools. Metabolomics needs for bioinformatics span through data and information management, raw analytical data processing, metabolomics standards and ontology, statistical analysis and data mining, data integration and mathematical modelling of metabolic networks within a framework of systems biology. The major approaches in metabolomics, along with the modern analytical tools used for data generation, are reviewed in the context of these specific bioinformatics needs.
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Cites
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Cited by
Methods of integrating data to uncover genotype-phenotype interactions
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Data processing for mass spectrometry-based metabolomics
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Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies
Jin, Q., & Ma, R. C. W. (2021) · Cells · doi:10.3390/cells10112832 · Cited by 252
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Metadata
- Authors
- Shulaev, V.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-03-07
- Volume
- 7
- Issue
- 2
- Pages
- 128-139
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2130466489
- Cited by
- 408
- References
- 109
- FWCI
- 4.67
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
