ALGORITHMS FOR AUTOMATIC PROCESSING OF DATA FROM MASS SPECTROMETRIC ANALYSES

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 最近发展起来的脂类分析的质谱学方法，特别是电喷雾电离(ESI)串联质谱仪，可以从少量的生物样品中识别和测量大量不同的脂类分子物种，但在短时间内产生大量的实验数据。处理这样的数据集，以便从中获得可理解的信息，需要生物信息学工具，而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应脂肪组学的策略。然而，脂类的结构多样性和复杂性也要求开发和应用专门针对处理脂类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.