ArticleAnalytical chemistry2011
SILACtor: software to enable dynamic SILAC studies.
Article in Analytical chemistry, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies.Journal of proteome research · 2023Article
- Accumulation of "Old Proteins" and the Critical Need for MS-based Protein Turnover Measurements in Aging and Longevity.Proteomics · 2020Review
- Protein Turnover in Aging and Longevity.Proteomics · 2018Review
- SILAC peptide ratio calculator: a tool for SILAC quantitation of peptides and post-translational modifications.Journal of proteome research · 2014Article
- Topograph, a software platform for precursor enrichment corrected global protein turnover measurements.Molecular & cellular proteomics : MCP · 2012Article
- Find pairs: the module for protein quantification of the PeakQuant software suite.Omics : a journal of integrative biology · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Stable isotope labeling by amino acids in cell culture (SILAC) is a versatile tool in proteomics that has been used to explore protein turnover on a large scale. However, these studies pose a significant undertaking that can be greatly simplified through the use of computational tools that automate the data analysis. While SILAC technology has enjoyed rapid adoption through the availability of several software tools, algorithms do not exist for the automated analysis of protein turnover data generated using SILAC technology. Presented here is a software tool, SILACtor, designed to trace and compare SILAC-labeled peptides across multiple time points. SILACtor is used to profile protein turnover rates for more than 500 HeLa cell proteins using a SILAC label-chase approach. Additionally, SILACtor contains a method for the automated generation of accurate mass and retention time inclusion lists that target peptides of interest showing fast or slow turnover rates relative to the other peptides observed in the samples. SILACtor enables improved protein turnover studies using SILAC technology and also provides a framework for features extensible to comparative SILAC analyses and targeted methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.