ReviewProteomics2016
Exploring the potential of public proteomics data.
Review in Proteomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 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
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An integrated landscape of protein expression in human cancer.Scientific data · 2021Pooled it
- A Global Assessment of the Transcription-Dependent Single Nucleotide Variants Relies on the Characteristics of RNA-Sequencing Technologies.Biomolecules · 2026Article
- A roadmap for equitable reuse of public microbiome data.Nature microbiology · 2025Review
- Revolutionizing multi-omics analysis with artificial intelligence and data processing.Quantitative biology (Beijing, China) · 2025Review
- Current Bioinformatics Tools in Precision Oncology.MedComm · 2025Review
- Proteomics and machine learning: Leveraging domain knowledge for feature selection in a skeletal muscle tissue meta-analysis.Heliyon · 2024Article
- FastProtein-an automated software forPeerJ · 2024Article
- Spectroscape enables real-time query and visualization of a spectral archive in proteomics.Nature communications · 2023Article
- PepQuery2 democratizes public MS proteomics data for rapid peptide searching.Nature communications · 2023Article
- Machine Learning on Large-Scale Proteomics Data Identifies Tissue and Cell-Type Specific Proteins.Journal of proteome research · 2023Article
- NeuroLINCS Proteomics: Defining human-derived iPSC proteomes and protein signatures of pluripotency.Scientific data · 2023Article
- An Optimized Comparative Proteomic Approach as a Tool in Neurodegenerative Disease Research.Cells · 2022Review
- Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas.Scientific data · 2022Article
- Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues.PLoS computational biology · 2022Article
- iProX in 2021: connecting proteomics data sharing with big data.Nucleic acids research · 2022Article
- AnnotaPipeline: An integrated tool to annotate eukaryotic proteins using multi-omics data.Frontiers in genetics · 2022Article
- Development of the "Applied Proteomics" Concept for Biotechnology Applications in Microalgae: Example of the Proteome Data inMarine drugs · 2021Review
- Article
- A Second Look at FAIR in Proteomic Investigations.Journal of proteome research · 2021Article
- Isolation of Industrial Important Bioactive Compounds from Microalgae.Molecules (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
In a global effort for scientific transparency, it has become feasible and good practice to share experimental data supporting novel findings. Consequently, the amount of publicly available MS-based proteomics data has grown substantially in recent years. With some notable exceptions, this extensive material has however largely been left untouched. The time has now come for the proteomics community to utilize this potential gold mine for new discoveries, and uncover its untapped potential. In this review, we provide a brief history of the sharing of proteomics data, showing ways in which publicly available proteomics data are already being (re-)used, and outline potential future opportunities based on four different usage types: use, reuse, reprocess, and repurpose. We thus aim to assist the proteomics community in stepping up to the challenge, and to make the most of the rapidly increasing amount of public proteomics data.
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.