ArticleDatabase : the journal of biological databases and curation2011
The NIDDK Central Repository at 8 years--ambition, revision, use and impact.
Article in Database : the journal of biological databases and curation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Article
- Closing the Gap Between Vision and Victory in Type 1 Diabetes: The NIDDK Human Islet Research Network (HIRN) Initiative.Diabetes · 2025Review
- A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles.PloS one · 2021Article
- Biobanking for Translational Diabetes Research in India.BioResearch open access · 2020Review
- Data Sharing in Neurosurgery and Neurology Journals.Cureus · 2018Article
- The biobank for the molecular classification of kidney disease: research translation and precision medicine in nephrology.BMC nephrology · 2017Article
- Dialyzer Reuse and Outcomes of High Flux Dialysis.PloS one · 2015Article
- Evaluation of urinary protein precipitation protocols for the multidisciplinary approach to the study of chronic pelvic pain research network.Journal of biomolecular techniques : JBT · 2014Article
- Big data from small data: data-sharing in the 'long tail' of neuroscience.Nature neuroscience · 2014Review
- 'What's in the NIDDK CDR?'--public query tools for the NIDDK central data repository.Database : the journal of biological databases and curation · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors.
Funding
Abstract
The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository makes data and biospecimens from NIDDK-funded research available to the broader scientific community. It thereby facilitates: the testing of new hypotheses without new data or biospecimen collection; pooling data across several studies to increase statistical power; and informative genetic analyses using the Repository's well-curated phenotypic data. This article describes the initial database plan for the Repository and its revision using a simpler model. Among the lessons learned were the trade-offs between the complexity of a database design and the costs in time and money of implementation; the importance of integrating consent documents into the basic design; the crucial need for linkage files that associate biospecimen IDs with the masked subject IDs used in deposited data sets; and the importance of standardized procedures to test the integrity data sets prior to distribution. The Repository is currently tracking 111 ongoing NIDDK-funded studies many of which include genotype data, and it houses over 5 million biospecimens of more than 25 types including serum, plasma, stool, urine, DNA, red blood cells, buffy coat and tissue. Repository resources have supported a range of biochemical, clinical, statistical and genetic research (188 external requests for clinical data and 31 for biospecimens have been approved or are pending). Genetic research has included GWAS, validation studies, development of methods to improve statistical power of GWAS and testing of new statistical methods for genetic research. We anticipate that the future impact of the Repository's resources on biomedical research will be enhanced by (i) cross-listing of Repository biospecimens in additional searchable databases and biobank catalogs; (ii) ongoing deployment of new applications for querying the contents of the Repository; and (iii) increased harmonization of procedures, data collection strategies, questionnaires etc. across both research studies and within the vocabularies used by different 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.