التفاصيل البيبلوغرافية
| العنوان: |
Computational methods to identify metabolic sub-networks based on metabolomic profiles. |
| المؤلفون: |
Frainay, Clément1, Jourdan, Fabien2 Fabien.Jourdan@toulouse.inra.fr |
| المصدر: |
Briefings in Bioinformatics. Jan2017, Vol. 18 Issue 1, p43-56. 14p. |
| مصطلحات موضوعية: |
METABOLOMICS, BIOINFORMATICS, BIOCHEMICAL variation, METABOLISM, GRAPH algorithms |
| مستخلص: |
Untargetedmetabolomics makes it possible to identify compounds that undergo significant changes in concentration in different experimental conditions. The resultingmetabolomic profile characterizes the perturbation concerned, but does not explain the underlying biochemical mechanisms. Bioinformaticsmethods make it possible to interpret results in light of the whole metabolism. This knowledge ismodelled into a network, which can be mined using algorithms that originate in graph theory. These algorithms can extract sub-networks related to the compounds identified. Several attempts have been made to adapt them to obtain more biologically meaningful results. However, there is still no consensus on this kind of analysis of metabolic networks. This review presents themain graph approaches used to interpretmetabolomic data usingmetabolic networks. Their advantages and drawbacks are discussed, and the impacts of their parameters are emphasized. We also provide some guidelines for relevant sub-network extraction and also suggest a range of applications formostmethods. [ABSTRACT FROM AUTHOR] |
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