Bioinformatics, data integration, and knowledge extraction from high throughput proteomics for enabling biomedical applications

项目摘要-研发3 该资源总体的目标是通过提供以下能力来广泛影响生物医学研究： 从小得多的样本中获得高质量的蛋白质组学数据，产生更多定量和全面的数据 测量，生成关于低丰度组分的改进和更广泛的信息，区分 目前有问题的多肽异构体，并使研究比目前大得多的样本集成为可能 通过提供测量吞吐量的增加来实现实用性。在这一续期中，技术与发展目标1和2项下的进展 将在蛋白质组的灵敏度、广度、质量和数量(即吞吐量)方面提供巨大的改进 数据。研发3的努力将通过先进的数据处理和处理算法实现这些能力 整合多个蛋白质组学和其他数据集，以帮助提取生物医学见解。R&D 3 将开发新的蛋白质鉴定和量化算法，这些算法需要有效地利用 研发中开发的超薄离子移动(IM)-MS平台的独特功能2.高精度和 非常高的精度和可重复性的碰撞截面(CCS)值来自超高的超高 分辨率IM测量将提供更有信心和更灵敏的多肽/蛋白质鉴定。一个 我们方法的关键方面是使用大量稳定的同位素标记的多肽来校准SLIM 超高分辨率IM分离带来更精确的肽碰撞截面信息。这些 同样的稳定同位素标记的多肽组也将用作校准剂，以实现对 它们的未标记类似物以及在某种程度上减少的所有多肽和蛋白质的广泛定量 精确度。TRDS 1和2项下的进展也将使翻译后的衡量变得更广泛 修饰，我们将使用它来推断样本中活跃的网络和路径。我们将继续 与这些网络一起开发我们的协作视觉分析工具，以促进探索和 对数据的解释。这些努力将建立在以前资源开发的基础上，并将得到促进 通过研发2项下的关键技术发展。这些努力结合在一起，将为快速 实施和初步评估新的蛋白质组学能力，提供更大和更丰富的数据集 挑战生物医学项目，并将其有效传播给研究界。

Project Summary – TR&D 3 The Resource overall has the goal of broadly impacting biomedical research by providing the abilities to: obtain high quality proteomics data from much smaller samples, produce more quantitative and comprehensive measurements, generate improved and more extensive information on low abundance components, distinguish presently problematic peptide isomers, and enable the study of much larger sample sets than presently practical by providing increases in measurement throughput. Advances under TR&Ds 1 and 2 in this renewal will provide large improvements in the sensitivity, breadth, quality, and quantity (i.e. throughput) of proteome data. The efforts of TR&D 3 will enable these capabilities through advanced algorithms for data processing and the integration of multiple proteomics and other data sets to aid the extraction of biomedical insights. TR&D 3 will develop new algorithms for protein identification and quantification that are needed to effectively utilize the unique capabilities of the SLIM ion mobility (IM)-MS platform developed in TR&D 2. Highly accurate and very highly precise and reproducible collision cross section (CCS) values derived from the SLIM ultra-high resolution IM measurements will provide more confident and sensitive identification of peptides/proteins. A key aspect of our approach is the use of large sets of stable isotope labeled peptides for the calibration of SLIM ultra-high resolution IM separations leading to more precise peptide collision cross section information. These same stable isotope labeled peptide sets will also serve as calibrants to enable highly accurate quantification of their unlabeled analogs as well as for broad quantification of all peptides and proteins at somewhat reduced accuracy. Advances under TR&Ds 1 and 2 will also enable a broader measurement of post-translational modifications, which we will use to infer networks and pathways active in the samples. We will continue to develop our collaborative visual analytic tool in conjunction with these networks to facilitate exploration and interpretation of the data. These efforts will build upon previous Resource developments and will be facilitated by key technological developments under TR&D 2. In combination, these efforts will provide a basis for rapid implementation and initial evaluation of new proteomics capabilities providing both larger and richer data sets for challenging biomedical projects, as well as their effective dissemination to the research community.