Name
Abstract | ||
|---|---|---|
Differences in tissues arising from a single organism are attributable, at least partially, to differing metabolic regimes. A highly topical instance of this is the Warburg effect in tumour development, whereby malignant tissue exhibits greatly altered metabolism compared to healthy tissue. To this end, we consider the emergent properties of two metabolomic datasets from a human glioma cell line (U87) and a human mesenchymal stem cell line (hMSC). Using a random matrix theory (RMT) approach, U87 is found to have a modular structure, whereas hMSC does not. The datasets are then compared using between groups comparison of principal components, and finally, a group of metabolites is found that remains highly correlated in both conditions. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-28792-3_12 | IPCAT |
Keywords | Field | DocType |
human glioma cell line,tailored strategy,metabolomic datasets,malignant tissue,healthy tissue,groups comparison,metabolic regime,altered metabolism,warburg effect,emergent property,human mesenchymal stem cell | Cell culture,Biology,Mesenchymal stem cell,U87,Glioma,Metabolomics,Metabolic network,Bioinformatics,Computational biology,Warburg effect,Principal component analysis | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kristen Feher | 1 | 1 | 0.73 |
| Kathrin Jürchott | 2 | 1 | 0.73 |
| Joachim Selbig | 3 | 772 | 93.34 |