ReviewBriefings in bioinformatics2013
Comparability and reproducibility of biomedical data.
Review in Briefings in bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses 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
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue.Bioinformatics (Oxford, England) · 2022Pooled it
- Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis.Scientific reports · 2019Pooled it
- The critical role of artificial intelligence and bioinformatics in accelerating peptide-based vaccine discovery for tackling global infectious diseases.Briefings in bioinformatics · 2026Review
- Knowledge-augmented pre-trained language models for biomedical relation extraction.BMC bioinformatics · 2025Article
- A Comparison of Three Automated Nucleic Acid Extraction Systems for Human Stool Samples.Microorganisms · 2024Article
- Best practices for data management and sharing in experimental biomedical research.Physiological reviews · 2024Review
- The five pillars of computational reproducibility: bioinformatics and beyond.Briefings in bioinformatics · 2023Article
- Orchestrating and sharing large multimodal data for transparent and reproducible research.Nature communications · 2021Article
- NPARS-A Novel Approach to Address Accuracy and Reproducibility in Genomic Data Science.Frontiers in big data · 2021Article
- Biomedical text mining for research rigor and integrity: tasks, challenges, directions.Briefings in bioinformatics · 2018Article
- DataPackageR: Reproducible data preprocessing, standardization and sharing using R/Bioconductor for collaborative data analysis.Gates open research · 2018Article
- A Bayesian approach for analysis of ordered categorical responses subject to misclassification.PloS one · 2018Article
- AVOCADO: Visualization of Workflow-Derived Data Provenance for Reproducible Biomedical Research.Computer graphics forum : journal of the European Association for Computer Graphics · 2016Article
- cSPider - Evaluation of a Free and Open-Source Automated Tool to Analyze Corticomotor Silent Period.PloS one · 2016Article
- Ease of adoption of clinical natural language processing software: An evaluation of five systems.Journal of biomedical informatics · 2015Article
- FAST: FAST Analysis of Sequences Toolbox.Frontiers in genetics · 2015Article
- Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancer.Physiological genomics · 2014Review
- Relevance relations for the concept of reproducibility.Journal of the Royal Society, Interface · 2014Article
- Minimum information about a biofilm experiment (MIABiE): standards for reporting experiments and data on sessile microbial communities living at interfaces.Pathogens and disease · 2014Review
- Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data.BMC bioinformatics · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
With the development of novel assay technologies, biomedical experiments and analyses have gone through substantial evolution. Today, a typical experiment can simultaneously measure hundreds to thousands of individual features (e.g. genes) in dozens of biological conditions, resulting in gigabytes of data that need to be processed and analyzed. Because of the multiple steps involved in the data generation and analysis and the lack of details provided, it can be difficult for independent researchers to try to reproduce a published study. With the recent outrage following the halt of a cancer clinical trial due to the lack of reproducibility of the published study, researchers are now facing heavy pressure to ensure that their results are reproducible. Despite the global demand, too many published studies remain non-reproducible mainly due to the lack of availability of experimental protocol, data and/or computer code. Scientific discovery is an iterative process, where a published study generates new knowledge and data, resulting in new follow-up studies or clinical trials based on these results. As such, it is important for the results of a study to be quickly confirmed or discarded to avoid wasting time and money on novel projects. The availability of high-quality, reproducible data will also lead to more powerful analyses (or meta-analyses) where multiple data sets are combined to generate new knowledge. In this article, we review some of the recent developments regarding biomedical reproducibility and comparability and discuss some of the areas where the overall field could be improved.
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.