Evidence map›Paper›PMID 35949917›Full record

ArticleF1000Research2022

DSMZCellDive: Diving into high-throughput cell line data.

Julia Koblitz, Wilhelm G Dirks, Sonja Eberth, Stefan Nagel, Laura Steenpass, Claudia Pommerenke

Abstract read
In one paragraph

Article in F1000Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Choosing the Right Cell Line for Acute Myeloid Leukemia (AML) Research.International journal of molecular sciences · 2023
    Review
  15. Article
  16. CCLHunter: An efficient toolkit for cancer cell line authentication.Computational and structural biotechnology journal · 2023
    Article
  17. Article
  18. Article
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.

Julia KoblitzLeibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, 38124, Germany.ORCID 0000-0002-7260-2129
Wilhelm G DirksLeibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, 38124, Germany.
Sonja EberthLeibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, 38124, Germany.ORCID 0000-0002-5796-2089
Stefan NagelLeibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, 38124, Germany.
Laura SteenpassLeibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, 38124, Germany.
Claudia PommerenkeLeibniz Institute DSMZ - German Collection of Microorganisms and Cell Cultures, Braunschweig, 38124, Germany.ORCID 0000-0002-9448-416X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human and animal cell lines serve as model systems in a wide range of life sciences such as cancer and infection research or drug screening. Reproducible data are highly dependent on authenticated, contaminant-free cell lines, no better delivered than by the official and certified biorepositories. Offering a web portal to high-throughput information on these model systems will facilitate working with and comparing to these references by data otherwise dispersed at different sources. We here provide DSMZCellDive to access a comprehensive data source on human and animal cell lines, freely available at celldive.dsmz.de. A wide variety of data sources are generated such as RNA-seq transcriptome data and STR (short tandem repeats) profiles. Several starting points ease entering the database via browsing, searching or visualising. This web tool is designed for further expansion on meta and high-throughput data to be generated in future. Explicated examples for the power of this novel tool include analysis of B-cell differentiation markers, homeo-oncogene expression, and measurement of genomic loss of heterozygosities by an enlarged STR panel of 17 loci. Sharing the data on cell lines by the biorepository itself will be of benefit to the scientific community  since it (1) supports the selection of appropriate model cell lines, (2) ensures reliability, (3) avoids misleading data, (4) saves on additional experimentals, and (5) serves as reference for genomic and gene expression data.

Indexed as

Microsatellite RepeatsNeoplasmsAnimalsCell LineHumansReproducibility of ResultsTranscriptomeDSMZHLAhomeoboxhuman and animal cell linesleukemiaLL-100lymphomaomics dataRNA-seqSTR

Identifiers

PMID35949917
PMCPMC9334839

What OpenQuestion holds

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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.