Evidence map›Paper›PMID 26627871›Full record

ReviewCritical reviews in biochemistry and molecular biology2016

Towards a compendium of essential genes - From model organisms to synthetic lethality in cancer cells.

Tianzuo Zhan, Michael Boutros

Open access · bronzeAbstract readReview
In one paragraph

Review in Critical reviews in biochemistry and molecular biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

22 citing papers in PubMed, 59 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. A Machine Learning Approach for Predicting Essentiality of Metabolic Genes.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  5. Article
  6. NAR genomics and bioinformatics · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Predicting gene essentiality inComputational and structural biotechnology journal · 2020
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

2 authors at 2 institutions in 1 country.

Tianzuo Zhana Department of Cell and Molecular Biology , Division of Signaling and Functional Genomics, Medical Faculty Mannheim, German Cancer Research Center (DKFZ), Heidelberg University , Heidelberg , Germany and.
Michael Boutrosa Department of Cell and Molecular Biology , Division of Signaling and Functional Genomics, Medical Faculty Mannheim, German Cancer Research Center (DKFZ), Heidelberg University , Heidelberg , Germany and.
German Cancer Research Center · DEUniversity Medical Centre Mannheim · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Essential genes are defined by their requirement to sustain life in cells or whole organisms. The systematic identification of essential gene sets not only allows insights into the fundamental building blocks of life, but may also provide novel therapeutic targets in oncology. The discovery of essential genes has been tightly linked to the development and deployment of various screening technologies. Here, we describe how gene essentiality was addressed in different eukaryotic model organisms, covering a range of organisms from yeast to mouse. We describe how increasing knowledge of evolutionarily divergent genomes facilitate identification of gene essentiality across species. Finally, the impact of gene essentiality and synthetic lethality on cancer research and the clinical translation of screening results are highlighted.

Indexed as

Genes, EssentialModels, BiologicalAnimalsComputational BiologyHumansNeoplasmsCancer researchCRISPR/Cas9essential genesgenetic interactionRNAiscreeningsynthetic lethality

Identifiers

PMID26627871
PMCPMC4819810
OpenAlexW2257942696

What OpenQuestion holds

Textmetadata
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.