Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 99-106 |
| Journal | European Journal of Lipid Science and Technology |
| Volume | 111 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2009 |
| MoE publication type | A2 Review article in a scientific journal |
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Keywords
- Bioinformatics
- lipidomics
- metabolomics
- pathway analysis
- systems biology
Cite this
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Bioinformatics and computational approaches applicable to lipidomics. / Orešič, Matej.
In: European Journal of Lipid Science and Technology, Vol. 111, No. 1, 2009, p. 99-106.Research output: Contribution to journal › Review Article › Scientific › peer-review
TY - JOUR
T1 - Bioinformatics and computational approaches applicable to lipidomics
AU - Orešič, Matej
PY - 2009
Y1 - 2009
N2 - Lipidomics owes its emergence to technologies developed over the past decade that empowered us with the ability to detect and quantify hundreds of intact lipid molecular species in parallel. One of the biggest current challenges of lipidomics is the elucidation of important pathobiological phenomena from the integration of large amounts of new data becoming available. In this respect, development of lipidomics as a field bears many similarities to the emergence and progress of genomics. Initial excitement over the ability to measure the expression of large numbers of genes in parallel was soon overshadowed by concerns over the ability to reliably analyze and interpret the expression data. This led to active research in the area of bioinformatics, which led to improved statistical methods as well as to new approaches for the analysis of transcriptome data in the pathway context. This review covers recent bioinformatics developments of relevance to analysis and interpretation of analytical lipidomics data, with the focus primarily on practical aspects of lipid bioinformatics.
AB - Lipidomics owes its emergence to technologies developed over the past decade that empowered us with the ability to detect and quantify hundreds of intact lipid molecular species in parallel. One of the biggest current challenges of lipidomics is the elucidation of important pathobiological phenomena from the integration of large amounts of new data becoming available. In this respect, development of lipidomics as a field bears many similarities to the emergence and progress of genomics. Initial excitement over the ability to measure the expression of large numbers of genes in parallel was soon overshadowed by concerns over the ability to reliably analyze and interpret the expression data. This led to active research in the area of bioinformatics, which led to improved statistical methods as well as to new approaches for the analysis of transcriptome data in the pathway context. This review covers recent bioinformatics developments of relevance to analysis and interpretation of analytical lipidomics data, with the focus primarily on practical aspects of lipid bioinformatics.
KW - Bioinformatics
KW - lipidomics
KW - metabolomics
KW - pathway analysis
KW - systems biology
U2 - 10.1002/ejlt.200800144
DO - 10.1002/ejlt.200800144
M3 - Review Article
VL - 111
SP - 99
EP - 106
JO - European Journal of Lipid Science and Technology
JF - European Journal of Lipid Science and Technology
SN - 1438-7697
IS - 1
ER -