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Flexible Quality Control for Protein Turnover Rates Using d2ome

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 integrati...

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Detalles Bibliográficos
Autores principales: Deberneh, Henock M., Sadygov, Rovshan G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649227/
https://www.ncbi.nlm.nih.gov/pubmed/37958536
http://dx.doi.org/10.3390/ijms242115553
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author Deberneh, Henock M.
Sadygov, Rovshan G.
author_facet Deberneh, Henock M.
Sadygov, Rovshan G.
author_sort Deberneh, Henock M.
collection PubMed
description 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.
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spelling pubmed-106492272023-10-25 Flexible Quality Control for Protein Turnover Rates Using d2ome Deberneh, Henock M. Sadygov, Rovshan G. Int J Mol Sci Article 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. MDPI 2023-10-25 /pmc/articles/PMC10649227/ /pubmed/37958536 http://dx.doi.org/10.3390/ijms242115553 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Deberneh, Henock M.
Sadygov, Rovshan G.
Flexible Quality Control for Protein Turnover Rates Using d2ome
title Flexible Quality Control for Protein Turnover Rates Using d2ome
title_full Flexible Quality Control for Protein Turnover Rates Using d2ome
title_fullStr Flexible Quality Control for Protein Turnover Rates Using d2ome
title_full_unstemmed Flexible Quality Control for Protein Turnover Rates Using d2ome
title_short Flexible Quality Control for Protein Turnover Rates Using d2ome
title_sort flexible quality control for protein turnover rates using d2ome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649227/
https://www.ncbi.nlm.nih.gov/pubmed/37958536
http://dx.doi.org/10.3390/ijms242115553
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