ArticleJournal of proteome research2015
State of the Human Proteome in 2014/2015 As Viewed through PeptideAtlas: Enhancing Accuracy and Coverage through the AtlasProphet.
Article in Journal of proteome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed.
- Article
- High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.bioRxiv : the preprint server for biology · 2025Article
- Evaluation of PE5 Entries on the Human Proteome Project Target List.Journal of proteome research · 2025Article
- Multiomics in silico analysis identifies TM4SF4 as a cell surface target in hepatocellular carcinoma.PloS one · 2025Article
- Evolution and implications of de novo genes in humans.Nature ecology & evolution · 2023Review
- The 2022 Report on the Human Proteome from the HUPO Human Proteome Project.Journal of proteome research · 2023Review
- MetaPep: A core peptide database for faster human gut metaproteomics database searches.Computational and structural biotechnology journal · 2023Article
- Autonomous action and cooperativity between the ONECUT2 transcription factor and its 3' untranslated region.Frontiers in cell and developmental biology · 2023Article
- Engineered SH2 Domains for Targeted Phosphoproteomics.ACS chemical biology · 2022Article
- The PeptideAtlas of a widely cultivated fish Labeo rohita: A resource for the Aquaculture Community.Scientific data · 2022Article
- Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases.International journal of molecular sciences · 2022Review
- Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project.Journal of proteome research · 2021Article
- Accessing NCBI data using the NCBI Sequence Viewer and Genome Data Viewer (GDV).Genome research · 2021Article
- Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project.Journal of proteome research · 2020Article
- A high-stringency blueprint of the human proteome.Nature communications · 2020Review
- Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis.Molecular cell · 2020Article
- Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization.International journal of molecular sciences · 2020Review
- The neXtProt knowledgebase in 2020: data, tools and usability improvements.Nucleic acids research · 2020Article
- Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome.Cell reports · 2019Article
- Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project.Journal of proteome research · 2019Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The Human PeptideAtlas is a compendium of the highest quality peptide identifications from over 1000 shotgun mass spectrometry proteomics experiments collected from many different laboratories, all reanalyzed through a uniform processing pipeline. The latest 2015-03 build contains substantially more input data than past releases, is mapped to a recent version of our merged reference proteome, and uses improved informatics processing and the development of the AtlasProphet to provide the highest quality results. Within the set of ∼20,000 neXtProt primary entries, 14,070 (70%) are confidently detected in the latest build, 5% are ambiguous, 9% are redundant, leaving the total percentage of proteins for which there are no mapping detections at just 16% (3166), all derived from over 133 million peptide-spectrum matches identifying more than 1 million distinct peptides using AtlasProphet to characterize and classify the protein matches. Improved handling for detection and presentation of single amino-acid variants (SAAVs) reveals the detection of 5326 uniquely mapping SAAVs across 2794 proteins. With such a large amount of data, the control of false positives is a challenge. We present the methodology and results for maintaining rigorous quality along with a discussion of the implications of the remaining sources of errors in the build.
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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.