Analysis and interpretation of complex lipidomic data using bioinformatic approaches

摘要: Analysis and interpretation of complex lipidomic data using bioinformatic approaches Lu Zhang Dissertation advisor: Jeffrey H. Chuang The field lipidomics has rapidly progressed since its inception only a decade ago. Technological revolutions in mass spectrometry, chromatography, computational biology now enables high-throughput high-accuracy quantification the cellular lipidome. One significant improvement these technologies is that lipids can be identified quantified as individual molecular species. Lipidomics provides an additional layer information to genomics proteomics opens new opportunity for furthering our understanding signaling networks physiology, which have broad therapeutic values. As with other ′omics sciences, are producing vast amounts data, require sophisticated statistical analysis interpretation. However, tools utilizing such sparse. complexity lipid metabolic systems fact enzymes remain poorly understood also present challenges lipidomics. focus my dissertation been development novel methods systematic study metabolism function human diseases data. In this dissertation, I first mathematical model describing cardiolipin molecii ular species distribution steady state relationship fatty acid chain compositions. Knowledge facilitates determination isomeric lipids, providing more detailed beyond current limits spectrometry technology. correlate profiles predict potential therapeutics. Second, studies mechanisms influencing phosphatidylcholine phosphatidylethanolamine architectures, respectively. describe approach examine dependence sn1 sn2 acyl regulatory mechanisms. Third, network inference illustrate dynamic ethanolamine glycerophospholipid remodeling. accurately robustly describes changes pulse-chase experiments. A key outcome deacylation reacylation rates chains determined, resulting explain well-known prevalence saturated unsaturated chains. Lastly, summarize remark on future