ReviewNature reviews. Genetics2016
Crowdsourcing biomedical research: leveraging communities as innovation engines.
Review in Nature reviews. Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 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
79 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mapping of Crowdsourcing in Health: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.The Lancet. Oncology · 2017Trial
- OpenChallenges: A FAIR-aligned, centralized platform for crowdsourced challenges in biomedical research.Patterns (New York, N.Y.) · 2026Article
- Benchmarking biomedical foundation models.Nature methods · 2026Review
- The SEA-AD DREAM Challenge: Community benchmarking human and AI agent solutions for Alzheimer's disease neuropathology prediction from single-nucleus transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Multimodal spatial omics: From data acquisition to computational integration.Patterns (New York, N.Y.) · 2026Review
- A Roadmap for the Future of Systems Biology in Cancer Research.Cancer research · 2025Review
- Cell-type deconvolution methods for spatial transcriptomics.Nature reviews. Genetics · 2025Review
- GHIST 2024: The First Genomic History Inference Strategies Tournament.Molecular biology and evolution · 2025Article
- Article
- Computational frameworks transform antagonism to synergy in optimizing combination therapies.NPJ digital medicine · 2025Review
- Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation.Frontiers in digital health · 2025Review
- Artificial Intelligence in Medicine and Imaging Applications.Current pharmaceutical design · 2025Review
- AI-empowered perturbation proteomics for complex biological systems.Cell genomics · 2024Article
- Molecular causality in the advent of foundation models.Molecular systems biology · 2024Review
- Expanding a Behavioral View on Digital Health Access: Drivers and Strategies to Promote Equity.Journal of medical Internet research · 2024Article
- Optimal linear ensemble of binary classifiers.Bioinformatics advances · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Computational Advancements in Cancer Combination Therapy Prediction.JCO precision oncology · 2023Article
19 more citing papers are in PubMed but not listed here.
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
The generation of large-scale biomedical data is creating unprecedented opportunities for basic and translational science. Typically, the data producers perform initial analyses, but it is very likely that the most informative methods may reside with other groups. Crowdsourcing the analysis of complex and massive data has emerged as a framework to find robust methodologies. When the crowdsourcing is done in the form of collaborative scientific competitions, known as Challenges, the validation of the methods is inherently addressed. Challenges also encourage open innovation, create collaborative communities to solve diverse and important biomedical problems, and foster the creation and dissemination of well-curated data repositories.
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.