Evidence map›Paper›PMID 21051335›Full record

ArticleNucleic acids research2011

IGRhCellID: integrated genomic resources of human cell lines for identification.

Cheng-Kai Shiau, De-Leung Gu, Chian-Feng Chen, Chi-Hung Lin, Yuh-Shan Jou

Abstract read
In one paragraph

Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. The Cellosaurus, a Cell-Line Knowledge Resource.Journal of biomolecular techniques : JBT · 2018
    Article
  5. Article
  6. Article
  7. Biomarker identification of hepatocellular carcinoma using a methodical literature mining strategy.Database : the journal of biological databases and curation · 2017
    Article
  8. Article
  9. 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

5 authors.

Cheng-Kai ShiauInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
De-Leung Gu
Chian-Feng Chen
Chi-Hung Lin
Yuh-Shan Jou

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell line identification is emerging as an essential method for every cell line user in research community to avoid using misidentified cell lines for experiments and publications. IGRhCellID (http://igrcid.ibms.sinica.edu.tw) is designed to integrate eight cell identification methods including seven methods (STR profile, gender, immunotypes, karyotype, isoenzyme profile, TP53 mutation and mutations of cancer genes) available in various public databases and our method of profiling genome alterations of human cell lines. With data validation of 11 small deleted genes in human cancer cell lines, profiles of genomic alterations further allow users to search for human cell lines with deleted gene to serve as indigenous knock-out cell model (such as SMAD4 in gene view), with amplified gene to be the cell models for testing therapeutic efficacy (such as ERBB2 in gene view) and with overlapped aberrant chromosomal loci for revealing common cancer genes (such as 9p21.3 homozygous deletion with co-deleted CDKN2A, CDKN2B and MTAP in chromosome view). IGRhCellID provides not only available methods for cell identification to help eradicating concerns of using misidentified cells but also designated genetic features of human cell lines for experiments.

Indexed as

Cell LineDatabases, FactualGenomicsCell Line, TumorGenesGenetic LociHumans

Identifiers

PMID21051335
PMCPMC3013678

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.