• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Computational intelligence methods for bioinformatics and biostatistics >SILACAnalyzer - A Tool for Differential Quantitation of Stable Isotope Derived Data
【24h】

SILACAnalyzer - A Tool for Differential Quantitation of Stable Isotope Derived Data

机译：SILACAnalyzer-稳定同位素衍生数据的差分定量分析工具

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Quantitative proteomics is a growing field where several experimental techniques such as those based around stable isotope labelling are reaching maturity. These advances require the parallel development of informatics tools to process and analyse the data, especially for high-throughput experiments seeking to quantify large numbers of proteins. We have developed a novel algorithm for the quantitative analysis of stable isotope-based proteomics data at the peptide level. Without prior formal identification of the peptides by MS/MS, the algorithm determines the mass charge ratio m/z and retention time t of stable isotope-labelled peptide pairs and calculates their relative ratios. It supports several non-proprietary XML input formats and requires only minimal parameter tuning and runs fully automated. We have tested its performance on a low complexity peptide sample in an initial study. In comparison to a manual analysis and an automated approach using MSQuant, it performs as well or better and therefore we believe it has utility for groups wishing to perform high-throughput experiments.
机译：定量蛋白质组学是一个不断发展的领域，其中一些实验技术（例如基于稳定同位素标记的实验技术）已经成熟。这些进步要求并行开发信息学工具来处理和分析数据，尤其是对于试图量化大量蛋白质的高通量实验。我们已经开发了一种新颖的算法，可以在肽水平上对基于同位素的稳定蛋白质组学数据进行定量分析。无需事先通过MS / MS正式鉴定这些肽，该算法即可确定稳定同位素标记的肽对的质荷比m / z和保留时间t，并计算其相对比。它支持几种非专有的XML输入格式，只需要最小的参数调整即可完全自动化地运行。在初步研究中，我们已经在低复杂度肽样品上测试了其性能。与使用MSQuant的手动分析和自动化方法相比，它的性能相同或更好，因此我们认为它对于希望执行高通量实验的小组很有用。

著录项

  • 来源
  • 会议地点 Genoa(IT);Genoa(IT)
  • 作者

    Lars Nilse; Marc Sturm; David Trudgian; M0ogjiborahman Salek; Paul F.G. Sims; Kathleen M. Carroll; Simon J. Hubbard;

  • 作者单位

    Faculty of Life Sciences, University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK,Wilhelm Schickard Institute for Computer Science, Eberhard Karls University, Tubingen, Sand 14, 72076 Tubingen, Germany;

    Wilhelm Schickard Institute for Computer Science, Eberhard Karls University, Tubingen, Sand 14, 72076 Tubingen, Germany;

    Centre for Cellular and Molecular Physiology, University of Oxford,Roosevelt Drive, Oxford 0X3 7BN, UK,Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford 0X1 3RE, UK;

    Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford 0X1 3RE, UK;

    Faculty of Life Sciences, Manchester Interdisciplinary Biocentre, 131 Princess Street, Manchester Ml 7DN, UK;

    Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, 131 Princess Street, Manchester Ml 7DN, UK;

    Faculty of Life Sciences, University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物工程学（生物技术）;人工智能理论;
  • 关键词

  • 入库时间 2022-08-26 14:04:25

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号