Title |
A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions
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Published in |
BMC Systems Biology, October 2013
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DOI | 10.1186/1752-0509-7-107 |
Pubmed ID | |
Authors |
Helen L Kotze, Emily G Armitage, Kieran J Sharkey, James W Allwood, Warwick B Dunn, Kaye J Williams, Royston Goodacre |
Abstract |
Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Portugal | 3 | 2% |
Switzerland | 2 | 1% |
Hungary | 1 | <1% |
Germany | 1 | <1% |
Brazil | 1 | <1% |
Sweden | 1 | <1% |
South Africa | 1 | <1% |
Singapore | 1 | <1% |
Iran, Islamic Republic of | 1 | <1% |
Other | 2 | 1% |
Unknown | 152 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 42 | 25% |
Researcher | 34 | 20% |
Student > Master | 23 | 14% |
Professor | 10 | 6% |
Professor > Associate Professor | 7 | 4% |
Other | 27 | 16% |
Unknown | 23 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 46 | 28% |
Biochemistry, Genetics and Molecular Biology | 26 | 16% |
Chemistry | 18 | 11% |
Medicine and Dentistry | 10 | 6% |
Computer Science | 8 | 5% |
Other | 28 | 17% |
Unknown | 30 | 18% |