ArticleJournal of proteome research2016
Testing and Validation of Computational Methods for Mass Spectrometry.
Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- NeuroMetBench: patient-aware evidence bounds for transcript-derived metabolic representations across cancer proteogenomic contexts.Functional & integrative genomics · 2026Article
- Mass Spectrometry-Based Validation of Chimeric RNAs.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Proteomic Profiling Towards a Better Understanding of Genetic Based Muscular Diseases: The Current Picture and a Look to the Future.Biomolecules · 2025Review
- Expert Algorithm for Substance Identification Using Mass Spectrometry: Statistical Foundations in Unimolecular Reaction Rate Theory.Journal of the American Society for Mass Spectrometry · 2023Article
- Expert Algorithm for Substance Identification Using Mass Spectrometry: Application to the Identification of Cocaine on Different Instruments Using Binary Classification Models.Journal of the American Society for Mass Spectrometry · 2023Article
- Triqler for Protein Summarization of Data from Data-Independent Acquisition Mass Spectrometry.Journal of proteome research · 2023Article
- Simulation of mass spectrometry-based proteomics data with Synthedia.Bioinformatics advances · 2023Article
- A Systematic Review of Metabolomic and Lipidomic Candidates for Biomarkers in Radiation Injury.Metabolites · 2020Review
- The impact of different sources of heterogeneity on loss of accuracy from genomic prediction models.Biostatistics (Oxford, England) · 2020Article
- ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies.Briefings in bioinformatics · 2020Article
- Simultaneous Improvement in the Precision, Accuracy, and Robustness of Label-free Proteome Quantification by Optimizing Data Manipulation Chains.Molecular & cellular proteomics : MCP · 2019Article
- pmartR: Quality Control and Statistics for Mass Spectrometry-Based Biological Data.Journal of proteome research · 2019Article
- Robust determination of differential abundance in shotgun proteomics using nonparametric statistics.Molecular omics · 2018Article
- Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing.Journal of proteome research · 2018Article
- Discovery of the Consistently Well-Performed Analysis Chain for SWATH-MS Based Pharmacoproteomic Quantification.Frontiers in pharmacology · 2018Article
- A Golden Age for Working with Public Proteomics Data.Trends in biochemical sciences · 2017Review
- A multicenter study benchmarks software tools for label-free proteome quantification.Nature biotechnology · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.
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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.