Bioinformatics and computational approaches applicable to lipidomics

Abstract

AbstractLipidomics 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.