Flexible Quality Control for Protein Turnover Rates Using d2ome.

Flexible Quality Control for Protein Turnover Rates Using d2ome.
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DOI:
10.3390/ijms242115553
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发表时间:
2023-10-25
影响因子:
5.6
通讯作者:
Sadygov RG
Sadygov RG
中科院分区:
生物学2区
文献类型:
--
作者:
Deberneh HM;Sadygov RG

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生物信息学工具用于从高通量重水标记样品的LC-MS数据估计体内蛋白质周转率。定量包括哺乳动物蛋白质组的复杂输入数据的LC-MS域中的峰检测和整合,这需要整合来自不同实验的结果。用于估计周转率的现有软件工具使用预定义的、内置的、严格的过滤标准来选择拟合良好的肽并确定蛋白质的周转率。过滤和质量测量的灵活控制将有助于减少波动和干扰对来自靶肽的信号的影响,同时保留足够数量的肽。这项工作描述了一种方法,灵活的错误控制和过滤措施,在计算工具d2 ome自动化蛋白质周转率。误差控制措施(基于光谱特性和信号特征)降低了标准差,并收紧了估计周转率的置信区间。
Bioinformatics tools are used to estimate in vivo protein turnover rates from the LC-MS data of heavy water labeled samples in high throughput. The quantification includes peak detection and integration in the LC-MS domain of complex input data of the mammalian proteome, which requires the integration of results from different experiments. The existing software tools for the estimation of turnover rate use predefined, built-in, stringent filtering criteria to select well-fitted peptides and determine turnover rates for proteins. The flexible control of filtering and quality measures will help to reduce the effects of fluctuations and interferences to the signals from target peptides while retaining an adequate number of peptides. This work describes an approach for flexible error control and filtering measures implemented in the computational tool d2ome for automating protein turnover rates. The error control measures (based on spectral properties and signal features) reduced the standard deviation and tightened the confidence intervals of the estimated turnover rates.
DOI: 10.1038/s41597-023-02537-w
发表时间: 2023-09-19
期刊: SCIENTIFIC DATA
影响因子: 9.8
作者:
Deberneh, Henock M.;Abdelrahman, Doaa R.;Verma, Sunil K.;Linares, Jennifer J.;Murton, Andrew J.;Russell, William K.;Kuyumcu-Martinez, Muge N.;Miller, Benjamin F.;Sadygov, Rovshan G.
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