Diversity Supplement for Alyssa Nitz for GM147653

单细胞蛋白质组学（SCP）正在迅速兴起，每个细胞可以定量超过1000种蛋白质。 仪器和样品制备方面的重大进步使SCP更加广泛 容易接近然而，数据采集方面的技术进步并没有与 计算工具。蛋白质组学算法的设计和优化的数据从批量 蛋白质组学，不适合SCP数据。我们的初步研究表明，来自SCP的数据 缺乏对当前蛋白质组学算法至关重要的许多特征。我们将戏剧性地 通过创建有史以来第一个 专用SCP搜索软件这将与改善SCP肽的倡议相结合 和蛋白质定量。这些算法改进将从一个大型语料库中获悉 收集并集中到第一个SCP数据档案中。

Single cell proteomics (SCP) is rapidly emerging and can quantify > 1000 proteins per cell. Significant advances in instrumentation and sample preparation are making SCP more broadly accessible. Yet technical advances in data acquisition have not been paired with advances to computational tools. Algorithms for proteomics were designed and optimized on data from bulk proteomics, and are ill-suited for SCP data. Our preliminary research shows that data from SCP lack many features that are critical for current proteomics algorithms. We will dramatically improve accuracy and coverage of the single cell proteome through creation of the first-ever dedicated SCP search software. This will be coupled with an initiative to improve SCP peptide and protein quantification. These algorithmic improvements will be informed from a large corpus of SCP data, gathered and centralized into the first SCP data archive.