Evidence map›Paper›PMID 34970894›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2021

[The identification of lung cancer gene-drug module based on multiplex networks algorithm].

Gang Zhou, Jie Gao

Open access · greenAbstract read
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 86% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 institution in 1 country.

Gang ZhouSchool of Science, Jiangnan University, Wuxi, Jiangsu 214122, P. R. China.
Jie GaoSchool of Science, Jiangnan University, Wuxi, Jiangsu 214122, P. R. China.
Jiangnan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using modular identification methods in gene-drug multiplex networks to infer new gene-drug associations can identify new therapeutic target genes for known drugs. In this paper, based on the gene expression data and drug response data of lung cancer in the genomics of drug sensitivity in cancer (GDSC) database, a multiple network algorithm is proposed. First, a heterogeneous network of genes of lung cancer and drugs in different cell lines is constructed, and then a network module identification method based on graph entropy is used. In this heterogeneous network, network modules are identified, and five lung cancer gene-drug association modules are identified through iterative convergence. Compared with other methods, the algorithm has better results in terms of running time, accuracy and robustness, and the identified modules have obvious biological significance. The research results in this article have guiding significance for the medication and treatment of lung cancer, and can provide references for the treatment of other diseases with the same targeted genes.

Indexed as

Lung NeoplasmsPharmaceutical PreparationsAlgorithmsGene Expression ProfilingGenes, NeoplasmHumansLungPharmaceutical Preparationsdrug responsegene expressionmodule identificationsimilarity network

Identifiers

PMID34970894
PMCPMC9927131
OpenAlexW4205800432

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.