Sadygov相关文献与解析，生知库 | 链接生命科学的每一步

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

利用重水代谢标记，通过量化两种质量同位素异构体的标记富集度，可以提高体内蛋白质周转的蛋白质组覆盖率。

doi:10.1038/s42004-023-00873-x

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

代谢

发表日期：2023

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A large-scale LC-MS dataset of murine liver proteome from time course of heavy water metabolic labeling

重水代谢标记时间过程中小鼠肝脏蛋白质组的大规模 LC-MS 数据集

期刊:Scientific Data

影响因子:5.8

doi:10.1038/s41597-023-02537-w

Henock M Deberneh, Doaa R Abdelrahman, Sunil K Verma, Jennifer J Linares, Andrew J Murton, William K Russell, Muge N Kuyumcu-Martinez, Benjamin F Miller, Rovshan G Sadygov

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发表日期：2023

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Retention Time Alignment for Protein Turnover Studies Using Heavy Water Metabolic Labeling

利用重水代谢标记进行蛋白质周转研究的保留时间校准

期刊:Journal of Proteome Research

影响因子:3.6

doi:10.1021/acs.jproteome.2c00592

Deberneh, Henock M; Sadygov, Rovshan G

代谢

发表日期：2023

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Using Heavy Mass Isotopomers for Protein Turnover in Heavy Water Metabolic Labeling

利用重水代谢标记中的重质量同位素异构体进行蛋白质周转

期刊:Journal of Proteome Research

影响因子:3.6

doi:10.1021/acs.jproteome.0c00873

Correction to "d2ome, Software for in Vivo Protein Turnover Analysis Using Heavy Water Labeling and LC-MS, Reveals Alterations of Hepatic Proteome Dynamics in a Mouse Model of NAFLD"

更正“d2ome，一款利用重水标记和液相色谱-质谱联用技术进行体内蛋白质周转分析的软件，揭示了非酒精性脂肪性肝病小鼠模型中肝脏蛋白质组动态的变化”

期刊:Journal of Proteome Research

影响因子:3.6

doi:10.1021/acs.jproteome.1c00698

Sadygov, Rovshan G; Avva, Jayant; Rahman, Mahbubur; Lee, Kwangwon; Ilchenko, Sergei; Kasumov, Takhar; Borzou, Ahmad

A novel estimator of the interaction matrix in Graphical Gaussian Model of omics data using the entropy of non-equilibrium systems

一种利用非平衡系统熵的组学数据图高斯模型中相互作用矩阵的新型估计方法

期刊:

影响因子:

doi:10.1093/bioinformatics/btaa894

Borzou, Ahmad; Sadygov, Rovshan G

发表日期：2021

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High-Resolution Mass Spectrometry for In Vivo Proteome Dynamics using Heavy Water Metabolic Labeling

利用重水代谢标记进行高分辨率质谱分析以研究体内蛋白质组动态变化

期刊:International Journal of Molecular Sciences

影响因子:4.9

doi:10.3390/ijms21217821

Timepoint Selection Strategy for In Vivo Proteome Dynamics from Heavy Water Metabolic Labeling and LC-MS

基于重水代谢标记和液相色谱-质谱联用技术的体内蛋白质组动态时间点选择策略

期刊:Journal of Proteome Research

影响因子:3.6

doi:10.1021/acs.jproteome.0c00023

Sadygov, Vugar R; Zhang, William; Sadygov, Rovshan G

代谢

发表日期：2020

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Turnover Rates and Numbers of Exchangeable Hydrogens in Deuterated Water Labeled Samples

氘代水标记样品中可交换氢的周转率和数量

Exact Integral Formulas for False Discovery Rate and the Variance of False Discovery Proportion

错误发现率及其方差的精确积分公式

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

利用重水代谢标记，通过量化两种质量同位素异构体的标记富集度，可以提高体内蛋白质周转的蛋白质组覆盖率。

A large-scale LC-MS dataset of murine liver proteome from time course of heavy water metabolic labeling

重水代谢标记时间过程中小鼠肝脏蛋白质组的大规模 LC-MS 数据集

Retention Time Alignment for Protein Turnover Studies Using Heavy Water Metabolic Labeling

利用重水代谢标记进行蛋白质周转研究的保留时间校准

Using Heavy Mass Isotopomers for Protein Turnover in Heavy Water Metabolic Labeling

利用重水代谢标记中的重质量同位素异构体进行蛋白质周转

Correction to "d2ome, Software for in Vivo Protein Turnover Analysis Using Heavy Water Labeling and LC-MS, Reveals Alterations of Hepatic Proteome Dynamics in a Mouse Model of NAFLD"

更正“d2ome，一款利用重水标记和液相色谱-质谱联用技术进行体内蛋白质周转分析的软件，揭示了非酒精性脂肪性肝病小鼠模型中肝脏蛋白质组动态的变化”

A novel estimator of the interaction matrix in Graphical Gaussian Model of omics data using the entropy of non-equilibrium systems

一种利用非平衡系统熵的组学数据图高斯模型中相互作用矩阵的新型估计方法

High-Resolution Mass Spectrometry for In Vivo Proteome Dynamics using Heavy Water Metabolic Labeling

利用重水代谢标记进行高分辨率质谱分析以研究体内蛋白质组动态变化

Timepoint Selection Strategy for In Vivo Proteome Dynamics from Heavy Water Metabolic Labeling and LC-MS

基于重水代谢标记和液相色谱-质谱联用技术的体内蛋白质组动态时间点选择策略