ReviewBritish journal of cancer2015
Big Data: the challenge for small research groups in the era of cancer genomics.
Review in British journal of cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations.Journal of medical systems · 2019Pooled it
- Oncopacket: integration of cancer research data using GA4GH phenopackets.Bioinformatics (Oxford, England) · 2025Article
- Increasing use of artificial intelligence in genomic medicine for cancer care- the promise and potential pitfalls.BJC reports · 2025Review
- A data management system for precision medicine.PLOS digital health · 2025Article
- Article
- Prevalence of Tumours and Tumour-like Lesions in Domestic and Exotic Animals from Lower Silesia and its Surrounds in Poland in 2014-2017.Journal of veterinary research · 2022Article
- Tracking Systems Used to Monitor the Performance and Activity Profile in Elite Team Sports.Sensors (Basel, Switzerland) · 2021Article
- Evaluation of prognostic biomarkers in a population-validated Finnish HNSCC patient cohort.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2021Article
- CNVIntegrate: the first multi-ethnic database for identifying copy number variations associated with cancer.Database : the journal of biological databases and curation · 2021Article
- dbNSFP v4: a comprehensive database of transcript-specific functional predictions and annotations for human nonsynonymous and splice-site SNVs.Genome medicine · 2020Article
- Deep learning of pharmacogenomics resources: moving towards precision oncology.Briefings in bioinformatics · 2020Article
- Common data elements of breast cancer for research databases: A systematic review.Journal of family medicine and primary care · 2020Review
- The International Cancer Genome Consortium Data Portal.Nature biotechnology · 2019Article
- Bioinformatics in Germany: toward a national-level infrastructure.Briefings in bioinformatics · 2019Article
- How Should Biobanks Prioritize and Diversify Biosample Collections? A 40-Year Scientific Publication Trend Analysis by the Type of Biosample.Omics : a journal of integrative biology · 2018Article
- Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.Experimental biology and medicine (Maywood, N.J.) · 2018Review
- Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned.Briefings in bioinformatics · 2017Article
- A cloud-based workflow to quantify transcript-expression levels in public cancer compendia.Scientific reports · 2016Article
- Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science.SpringerPlus · 2016Review
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 at 2 institutions in 2 countries.
Funding
Abstract
In the past decade, cancer research has seen an increasing trend towards high-throughput techniques and translational approaches. The increasing availability of assays that utilise smaller quantities of source material and produce higher volumes of data output have resulted in the necessity for data storage solutions beyond those previously used. Multifactorial data, both large in sample size and heterogeneous in context, needs to be integrated in a standardised, cost-effective and secure manner. This requires technical solutions and administrative support not normally financially accounted for in small- to moderate-sized research groups. In this review, we highlight the Big Data challenges faced by translational research groups in the precision medicine era; an era in which the genomes of over 75,000 patients will be sequenced by the National Health Service over the next 3 years to advance healthcare. In particular, we have looked at three main themes of data management in relation to cancer research, namely (1) cancer ontology management, (2) IT infrastructures that have been developed to support data management and (3) the unique ethical challenges introduced by utilising Big Data in research.
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.