ALGORITHMS FOR AUTOMATIC PROCESSING OF DATA FROM MASS SPECTROMETRIC ANALYSES

该子项目是利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 最近开发的用于脂质分析的质谱方法，特别是电喷雾电离（ESI）串联质谱，允许从少量生物样品中识别和测量大量不同的脂质分子种类，但在短暂的间隔内产生大量的实验数据。处理这样的数据集，以便从它们中获得可理解的信息需要生物信息学工具，并且为蛋白质组学和基因组学开发的算法提供了一些可以直接适用于脂质组学的策略。然而，脂质的结构多样性和复杂性也需要开发和应用专门针对处理脂质分析数据的新算法和软件工具。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Recently developed mass spectrometric methods for lipid analyses, especially electrospray ionization (ESI) tandem mass spectrometry, permit identification and measurement of an enormous variety of distinct lipid molecular species from small amounts of biological samples but generate a huge amount of experimental data within a brief interval. Processing such data sets so that comprehensible information is derived from them requires bioinformatics tools, and algorithms developed for proteomics and genomics have provided some strategies that can be directly adapted to lipidomics. The structural diversity and complexity of lipids, however, also requires the development and application of new algorithms and software tools that are specifically directed at processing data from lipid analyses.