Evidence map›Paper›PMID 24608173›Full record

ArticleDatabase : the journal of biological databases and curation2014

NCG 4.0: the network of cancer genes in the era of massive mutational screenings of cancer genomes.

Omer An, Vera Pendino, Matteo D'Antonio, Emanuele Ratti, Marco Gentilini, Francesca D Ciccarelli

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

36 citing papers in PubMed, 67 citations in OpenAlex.

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  8. Rapid preliminary purity evaluation of tumor biopsies using deep learning approach.Computational and structural biotechnology journal · 2020
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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 at 2 institutions in 2 countries.

Omer AnDepartment of Experimental Oncology, European Institute of Oncology, IFOM-IEO Campus, Via Adamello 16, 20139 Milan, Italy and Division of Cancer Studies, King's College London, London SE1 1UL, UK.
Vera Pendino
Matteo D'Antonio
Emanuele Ratti
Marco Gentilini
Francesca D Ciccarelli
King's College London · GBEuropean Institute of Oncology · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

NCG 4.0 is the latest update of the Network of Cancer Genes, a web-based repository of systems-level properties of cancer genes. In its current version, the database collects information on 537 known (i.e. experimentally supported) and 1463 candidate (i.e. inferred using statistical methods) cancer genes. Candidate cancer genes derive from the manual revision of 67 original publications describing the mutational screening of 3460 human exomes and genomes in 23 different cancer types. For all 2000 cancer genes, duplicability, evolutionary origin, expression, functional annotation, interaction network with other human proteins and with microRNAs are reported. In addition to providing a substantial update of cancer-related information, NCG 4.0 also introduces two new features. The first is the annotation of possible false-positive cancer drivers, defined as candidate cancer genes inferred from large-scale screenings whose association with cancer is likely to be spurious. The second is the description of the systems-level properties of 64 human microRNAs that are causally involved in cancer progression (oncomiRs). Owing to the manual revision of all information, NCG 4.0 constitutes a complete and reliable resource on human coding and non-coding genes whose deregulation drives cancer onset and/or progression. NCG 4.0 can also be downloaded as a free application for Android smart phones. Database URL: http://bio.ieo.eu/ncg/.

Indexed as

Databases, GeneticGene Regulatory NetworksSoftwareGene Expression ProfilingGene Expression Regulation, NeoplasticGenetic Association StudiesGenome, HumanHumansInternetMicroRNAsMutationNeoplasmsSearch EngineMicroRNAs

Identifiers

PMID24608173
PMCPMC3948431
OpenAlexW2111803340

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.