Evidence map›Paper›PMID 39417504›Full record

ArticleNucleic acids research2024

What is the real value of omics data? Enhancing research outcomes and securing long-term data excellence.

Eva Price, Felix Feyertag, Thomas Evans, James Miskin, Kyriacos Mitrophanous, Duygu Dikicioglu

Abstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Article
  2. Target identification and assessment in the era of AI.Nature reviews. Drug discovery · 2026
    Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. 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

6 authors.

Eva PriceDepartment of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, UK.
Felix FeyertagOxford Biomedica (UK) Ltd, Windrush Court, Transport Way, Oxford OX4 6LT, UK.
Thomas EvansOxford Biomedica (UK) Ltd, Windrush Court, Transport Way, Oxford OX4 6LT, UK.
James MiskinOxford Biomedica (UK) Ltd, Windrush Court, Transport Way, Oxford OX4 6LT, UK.
Kyriacos MitrophanousOxford Biomedica (UK) Ltd, Windrush Court, Transport Way, Oxford OX4 6LT, UK.
Duygu DikiciogluDepartment of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, UK.ORCID 0000-0002-3018-4790

Funding

Biotechnology and Biological Sciences Research Council BB/W009420/1UCLUKRI
6 · The paper itself

Abstract

A wealth of high-throughput biological data, of which omics constitute a significant fraction, has been made publicly available in repositories over the past decades. These data come in various formats and cover a range of species and research areas providing insights into the complexities of biological systems; the public repositories hosting these data serve as multifaceted resources. The potentially greater value of these data lies in their secondary utilization as the deployment of data science and artificial intelligence in biology advances. Here, we critically evaluate challenges in secondary data use, focusing on omics data of human embryonic kidney cell lines available in public repositories. The emerging issues are obstacles faced by secondary data users across diverse domains as they concern platforms and repositories, which accept deposition of data irrespective of their species type. The evolving landscape of data-driven research in biology prompts re-evaluation of open access data curation and submission procedures to ensure that these challenges do not impede novel research opportunities through data exploitation. This paper aims to draw attention to widespread issues with data reporting and encourages data owners to meticulously curate submissions to maximize not only their immediate research impact but also the long-term legacy of datasets.

Indexed as

GenomicsComputational BiologyData CurationHEK293 CellsHumansProteomics

Identifiers

PMID39417504
PMCPMC11551742

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.