ReviewProteomics2015
Computational phosphoproteomics: from identification to localization.
Review in Proteomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Estimating the total number of phosphoproteins and phosphorylation sites in eukaryotic proteomes.GigaScience · 2017Pooled it
- Computational approaches to identify sites of phosphorylation.Proteomics · 2024Review
- Phosphoproteomic Approaches for Identifying Phosphatase and Kinase Substrates.Molecules (Basel, Switzerland) · 2023Review
- Phosphorylation of GntR reduces Streptococcus suis oxidative stress resistance and virulence by inhibiting NADH oxidase transcription.PLoS pathogens · 2023Article
- Shared and unique phosphoproteomics responses in skeletal muscle from exercise models and in hyperammonemic myotubes.iScience · 2022Article
- Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation.Journal of proteome research · 2022Article
- Proteomics and phosphoproteomics datasets of a muscle-specific STIM1 loss-of-function mouse model.Data in brief · 2022Article
- Article
- Detection and Characterization of Catechol Quinone-Derived Protein Adducts Using Biomolecular Mass Spectrometry.Frontiers in chemistry · 2019Review
- The Pivotal Role of Protein Phosphorylation in the Control of Yeast Central Metabolism.G3 (Bethesda, Md.) · 2017Article
- The diverse and expanding role of mass spectrometry in structural and molecular biology.The EMBO journal · 2016Review
- Phosphoproteome Discovery in Human Biological Fluids.Proteomes · 2016Review
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 at 2 institutions in 1 country.
Funding
Abstract
Analysis of the phosphoproteome by MS has become a key technology for the characterization of dynamic regulatory processes in the cell, since kinase and phosphatase action underlie many major biological functions. However, the addition of a phosphate group to a suitable side chain often confounds informatic analysis by generating product ion spectra that are more difficult to interpret (and consequently identify) relative to unmodified peptides. Collectively, these challenges have motivated bioinformaticians to create novel software tools and pipelines to assist in the identification of phosphopeptides in proteomic mixtures, and help pinpoint or "localize" the most likely site of modification in cases where there is ambiguity. Here we review the challenges to be met and the informatics solutions available to address them for phosphoproteomic analysis, as well as highlighting the difficulties associated with using them and the implications for data standards.
Indexed as
Identifiers
What OpenQuestion holds
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.