ReviewProteomics. Clinical applications2015
Identifying novel biomarkers through data mining-a realistic scenario?
Review in Proteomics. Clinical applications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation.PLoS computational biology · 2024Pooled it
- Network-based integration of metabolomics data from large-scale repositories.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Facilitating analysis and dissemination of proteomics data through metadata integration in MaxQuant.Nature communications · 2025Article
- Simplifying Data Analysis in Biomedical Research: An Automated, User-Friendly Tool.Methods and protocols · 2024Article
- lesSDRF is more: maximizing the value of proteomics data through streamlined metadata annotation.Nature communications · 2023Article
- The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences.Nucleic acids research · 2022Article
- A proteomics sample metadata representation for multiomics integration and big data analysis.Nature communications · 2021Review
- An Overview of Genomics, Phylogenomics and Proteomics Approaches in Ascomycota.Life (Basel, Switzerland) · 2020Review
- Toward a Sample Metadata Standard in Public Proteomics Repositories.Journal of proteome research · 2020Article
- Proteomics study of silver nanoparticles on Caco-2 cells.Toxicology in vitro : an international journal published in association with BIBRA · 2018Article
- A Golden Age for Working with Public Proteomics Data.Trends in biochemical sciences · 2017Review
- Article
- Biomarker discovery in mass spectrometry-based urinary proteomics.Proteomics. Clinical applications · 2016Review
- 2016 update of the PRIDE database and its related tools.Nucleic acids research · 2016Article
- Exploring the potential of public proteomics data.Proteomics · 2016Review
- The potential clinical impact of the release of two drafts of the human proteome.Expert review of proteomics · 2015Article
- Proteomic repository data submission, dissemination, and reuse: key messages.Expert review of proteomicsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
In this article we discuss the requirements to use data mining of published proteomics datasets to assist proteomics-based biomarker discovery, the use of external data integration to solve the issue of inadequate small sample sizes and finally, we try to estimate the probability that new biomarkers will be identified through data mining alone.
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.