Evidence map›Paper›PMID 39202109›Full record

ArticleEntropy (Basel, Switzerland)2024

Non-Coding RNAs Extended Omnigenic Module of Cancers.

Jie Li, Bingbo Wang, Xiujuan Ma

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Jie LiSchool of Computer Science and Technology, Xidian University, Xi'an 710119, China.
Bingbo WangSchool of Computer Science and Technology, Xidian University, Xi'an 710119, China.ORCID 0000-0002-1808-1852
Xiujuan MaSchool of Computer Science and Technology, Xidian University, Xi'an 710119, China.

Funding

National Natural Science Foundation of China No. 62172318, 62372349, & 62132015
6 · The paper itself

Abstract

The emergence of cancers involves numerous coding and non-coding genes. Understanding the contribution of non-coding RNAs (ncRNAs) to the cancer neighborhood is crucial for interpreting the interaction between molecular markers of cancer. However, there is a lack of systematic studies on the involvement of ncRNAs in the cancer neighborhood. In this paper, we construct an interaction network which encompasses multiple genes. We focus on the fundamental topological indicator, namely connectivity, and evaluate its performance when applied to cancer-affected genes using statistical indices. Our findings reveal that ncRNAs significantly enhance the connectivity of affected genes and mediate the inclusion of more genes in the cancer module. To further explore the role of ncRNAs in the network, we propose a connectivity-based method which leverages the bridging function of ncRNAs across cancer-affected genes and reveals the non-coding RNAs extended omnigenic module (NeOModule). Topologically, this module promotes the formation of cancer patterns involving ncRNAs. Biologically, it is enriched with cancer pathways and treatment targets, providing valuable insights into disease relationships.

Indexed as

cancer moduleconnectivity patternheterogeneous networknon-coding RNAs

Identifiers

PMID39202109
PMCPMC11353529

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.