ArticleHuman genetics2011
Realizing the promise of population biobanks: a new model for translation.
Article in Human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed.
- Human milk: insights on cell composition, organoids and emerging applications.Pediatric research · 2026Review
- Impact of an evolving classification system on diffuse glioma repositories: experience from the Sydney brain tumour bank.Journal of neuro-oncology · 2026Article
- How the world of biobanking is changing with artificial intelligence.Frontiers in digital health · 2025Review
- Infrastructuring European scientific integration: Heterogeneous meanings of the European biobanking infrastructure BBMRI-ERIC.Social studies of science · 2023Article
- The social licence for data-intensive health research: towards co-creation, public value and trust.BMC medical ethics · 2021Review
- Engaged genomic science produces better and fairer outcomes: an engagement framework for engaging and involving participants, patients and publics in genomics research and healthcare implementation.Wellcome open research · 2021Article
- The ECOUTER methodology for stakeholder engagement in translational research.BMC medical ethics · 2017Article
- If you build it, they will come: unintended future uses of organised health data collections.BMC medical ethics · 2016Review
- DNA Source Selection for Downstream Applications Based on DNA Quality Indicators Analysis.Biopreservation and biobanking · 2016Article
- Closure of a human tissue biobank: individual, institutional, and field expectations during cycles of promise and disappointment.New genetics and society · 2015Article
- Toward a roadmap in global biobanking for health.European journal of human genetics : EJHG · 2012Article
- Evidence from the scene: paramedic perspectives on involvement in out-of-hospital research.Annals of emergency medicine · 2012Article
- Implementation of proteomic biomarkers: making it work.European journal of clinical investigation · 2012Article
- Situationally-sensitive knowledge translation and relational decision making in hyperacute stroke: a qualitative study.PloS one · 2012Article
- The art and science of biobanking.Human genetics · 2011Article
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
The promise of science lies in expectations of its benefits to societies and is matched by expectations of the realisation of the significant public investment in that science. In this paper, we undertake a methodological analysis of the science of biobanking and a sociological analysis of translational research in relation to biobanking. Part of global and local endeavours to translate raw biomedical evidence into practice, biobanks aim to provide a platform for generating new scientific knowledge to inform development of new policies, systems and interventions to enhance the public's health. Effectively translating scientific knowledge into routine practice, however, involves more than good science. Although biobanks undoubtedly provide a fundamental resource for both clinical and public health practice, their potentiating ontology--that their outputs are perpetually a promise of scientific knowledge generation--renders translation rather less straightforward than drug discovery and treatment implementation. Biobanking science, therefore, provides a perfect counterpoint against which to test the bounds of translational research. We argue that translational research is a contextual and cumulative process: one that is necessarily dynamic and interactive and involves multiple actors. We propose a new multidimensional model of translational research which enables us to imagine a new paradigm: one that takes us from bench to bedside to backyard and beyond, that is, attentive to the social and political context of translational science, and is cognisant of all the players in that process be they researchers, health professionals, policy makers, industry representatives, members of the public or research participants, amongst others.
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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.