ArticleMethods (San Diego, Calif.)2013
Computer aided manual validation of mass spectrometry-based proteomic data.
Article in Methods (San Diego, Calif.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed.
- Article
- Phosphoproteomics identifies microglial Siglec-F inflammatory response during neurodegeneration.Molecular systems biology · 2020Article
- Article
- Microtubule-Based Control of Motor-Clutch System Mechanics in Glioma Cell Migration.Cell reports · 2018Article
- Phosphorylation of human TRM9L integrates multiple stress-signaling pathways for tumor growth suppression.Science advances · 2018Article
- Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow.Nature communications · 2018Article
- Article
- Article
- Quantitative Phosphoproteomics Reveals Wee1 Kinase as a Therapeutic Target in a Model of Proneural Glioblastoma.Molecular cancer therapeutics · 2016Article
- Early signaling dynamics of the epidermal growth factor receptor.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- PTP1B-dependent regulation of receptor tyrosine kinase signaling by the actin-binding protein Mena.Molecular biology of the cell · 2015Article
- Mass spectrometry-based methods for identifying oxidized proteins in disease: advances and challenges.Biomolecules · 2015Review
- MARQUIS: a multiplex method for absolute quantification of peptides and posttranslational modifications.Nature communications · 2015Article
- Quantitative Profiling of Lysine Acetylation Reveals Dynamic Crosstalk between Receptor Tyrosine Kinases and Lysine Acetylation.PloS one · 2015Article
- Quantitative analysis of signaling networks across differentially embedded tumors highlights interpatient heterogeneity in human glioblastoma.Journal of proteome research · 2014Article
- Article
- System level dynamics of post-translational modifications.Current opinion in biotechnology · 2014Review
- A developmentally regulated translational control pathway establishes the meiotic chromosome segregation pattern.Genes & development · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics.
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.