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Software Packages for Shotgun Lipidomics

4 BIOINFORMATICS FOR LIPID NETWORK/PATHWAY ANALYSIS AND MODELING [Pg.139]

2 Simulatioii of Lipidomics Data for Interpretation of Biosynthesis Pathways [Pg.140]

One of the attempts for the purpose has been the recent development in dynamic or steady-state simulation of the obtained lipidomics data [58-61], The researchers clustered the lipid classes and individual molecular species involved in the biosynthesis of a particular lipid class and utilized the known biosynthesis and/or remodeling pathways to simulate the ion profiles of the lipid class of interest in order to achieve the best match between the simulated and determined ion spectra. Owing to the large set of lipidomics data, numerous parameters involving the biosynthesis pathways can be obtained from the simulation. These parameters are largely associated with biological functions through the model used for simulation. [Pg.140]

This approach was extensively validated by the comparison of individual simulated TAG species with those obtained from lipidomics analysis [61]. The simulated K parameters represent the relative contributions of the different DAG pools resulting from the PA, MAG, and PI (PC) pathways to TAG synthesis. Accordingly, the bioinformatic simulation provides a powerful vehicle to determine altered TAG biosynthesis pathways under pathophysiological conditions. [Pg.142]

This type of bioinformatic simulation was also applied to the PC and PE biosyntheses [60]. From these studies, it is clearly demonstrated that through simulation, the following information can be assessed  [Pg.142]


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