Evidence map›Paper›PMID 29636096›Full record

ReviewHuman genomics2018

The development of large-scale de-identified biomedical databases in the age of genomics-principles and challenges.

Fida K Dankar, Andrey Ptitsyn, Samar K Dankar

Abstract readReview
In one paragraph

Review in Human genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. New approaches in developing medicinal herbs databases.Database : the journal of biological databases and curation · 2023
    Review
  6. Article
  7. Profit versus Quality: The Enigma of Scientific Wellness.Journal of personalized medicine · 2022
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Informed Consent in Biomedical Research.Computational and structural biotechnology journal · 2019
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fida K DankarCollege of IT, UAEU, Al Ain, UAE. fida.dankar@uaeu.ac.ae.ORCID 0000-0002-1248-3295
Andrey PtitsynGloucester Marine Genomics Institute, Gloucester, MA, USA.
Samar K DankarFaculty of Sciences, University of Balamand, Souk El Ghareb, Lebanon.

Funding

United Arab Emirates University 31T084
6 · The paper itself

Abstract

Contemporary biomedical databases include a wide range of information types from various observational and instrumental sources. Among the most important features that unite biomedical databases across the field are high volume of information and high potential to cause damage through data corruption, loss of performance, and loss of patient privacy. Thus, issues of data governance and privacy protection are essential for the construction of data depositories for biomedical research and healthcare. In this paper, we discuss various challenges of data governance in the context of population genome projects. The various challenges along with best practices and current research efforts are discussed through the steps of data collection, storage, sharing, analysis, and knowledge dissemination.

Indexed as

Databases, GeneticGenomicsBiomedical ResearchHumansBiomedical databaseData governanceData privacyWhole genome sequencing

Identifiers

PMID29636096
PMCPMC5894154

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.