Wheelock Craig E, Goto Susumu, Yetukuri Laxman, D'Alexandri Fabio Luiz, Klukas Christian, Schreiber Falk, Oresic Matej
Department of Medical Biochemistry and Biophysics, Division of Physical Chemistry II, Karolinska Institutet, Stockholm, Sweden.
Methods Mol Biol. 2009;580:339-68. doi: 10.1007/978-1-60761-325-1_19.
Owing to their importance in cellular physiology and pathology as well as to recent technological advances, the study of lipids has reemerged as a major research target. However, the structural diversity of lipids presents a number of analytical and informatics challenges. The field of lipidomics is a new postgenome discipline that aims to develop comprehensive methods for lipid analysis, necessitating concomitant developments in bioinformatics. The evolving research paradigm requires that new bioinformatics approaches accommodate genomic as well as high-level perspectives, integrating genome, protein, chemical and network information. The incorporation of lipidomics information into these data structures will provide mechanistic understanding of lipid functions and interactions in the context of cellular and organismal physiology. Accordingly, it is vital that specific bioinformatics methods be developed to analyze the wealth of lipid data being acquired. Herein, we present an overview of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and application of its tools to the analysis of lipid data. We also describe a series of software tools and databases (KGML-ED, VANTED, MZmine, and LipidDB) that can be used for the processing of lipidomics data and biochemical pathway reconstruction, an important next step in the development of the lipidomics field.
由于脂质在细胞生理学和病理学中的重要性以及近期的技术进步，脂质研究已再度成为一个主要的研究目标。然而，脂质的结构多样性带来了许多分析和信息学方面的挑战。脂质组学领域是一门新兴的后基因组学科，旨在开发全面的脂质分析方法，这就需要生物信息学随之发展。不断演变的研究范式要求新的生物信息学方法既要考虑基因组层面，也要兼顾高层次视角，整合基因组、蛋白质、化学和网络信息。将脂质组学信息纳入这些数据结构，将有助于在细胞和生物体生理学背景下，从机制上理解脂质的功能和相互作用。因此，开发特定的生物信息学方法来分析所获取的大量脂质数据至关重要。在此，我们概述了京都基因与基因组百科全书（KEGG）数据库及其工具在脂质数据分析中的应用。我们还介绍了一系列可用于脂质组学数据处理和生化途径重建的软件工具和数据库（KGML-ED、VANTED、MZmine和LipidDB），这是脂质组学领域发展的重要下一步。
