Fahy Eoin, Cotter Dawn, Byrnes Robert, Sud Manish, Maer Andrea, Li Joshua, Nadeau David, Zhau Yihua, Subramaniam Shankar
San Diego Supercomputer Center, University of California, San Diego, La Jolla, California, USA.
Methods Enzymol. 2007;432:247-73. doi: 10.1016/S0076-6879(07)32011-9.
Lipids are recognized as key participants in the regulation and control of cellular function, having important roles in signal transduction processes. The diversity in lipid chemical structure presents a challenge for establishing practical methods to generate and manage high volumes of complex data that translate into a snapshot of cellular lipid changes. The need for high-quality bioinformatics to manage and integrate experimental data becomes imperative at several levels: (1) definition of lipid classification and ontologies, (2) relational database design, (3) capture and automated pipelining of experimental data, (4) efficient management of metadata, (5) development of lipid-centric search tools, (6) analysis and visual display of results, and (7) integration of the lipid knowledge base into biochemical pathways and interactive maps. This chapter describes the recent contributions of the bioinformatics core of the LIPID MAPS consortium toward achieving these objectives.
脂质被认为是细胞功能调节和控制的关键参与者，在信号转导过程中发挥着重要作用。脂质化学结构的多样性为建立实用方法以生成和管理大量复杂数据带来了挑战，这些数据可转化为细胞脂质变化的快照。在多个层面上，对高质量生物信息学来管理和整合实验数据的需求变得至关重要：（1）脂质分类和本体的定义，（2）关系数据库设计，（3）实验数据的捕获和自动化流水线处理，（4）元数据的有效管理，（5）以脂质为中心的搜索工具的开发，（6）结果的分析和可视化显示，以及（7）将脂质知识库整合到生化途径和交互式图谱中。本章描述了LIPID MAPS联盟生物信息学核心在实现这些目标方面的最新贡献。
