Evidence map›Paper›PMID 30769902›Full record

ArticleGenes2019

Analysis of Topological Parameters of Complex Disease Genes Reveals the Importance of Location in a Biomolecular Network.

Xiaohui Zhao, Zhi-Ping Liu

Abstract read
In one paragraph

Article in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  13. Investigation of the Active Ingredients and Mechanism ofDrug design, development and therapy · 2021
    Article
  14. Article
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  17. Essential gene prediction inComputational and structural biotechnology journal · 2020
    Article
  18. G Protein-Coupled Receptor Systems and Their Role in Cellular Senescence.Computational and structural biotechnology journal · 2019
    Review
  19. 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

2 authors.

Xiaohui ZhaoDepartment of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China. zhaoxiaohui199612@163.com.
Zhi-Ping LiuDepartment of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China. zpliu@sdu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Network biology and medicine provide unprecedented opportunities and challenges for deciphering disease mechanisms from integrative viewpoints. The disease genes and their products perform their dysfunctions via physical and biochemical interactions in the form of a molecular network. The topological parameters of these disease genes in the interactome are of prominent interest to the understanding of their functionality from a systematic perspective. In this work, we provide a systems biology analysis of the topological features of complex disease genes in an integrated biomolecular network. Firstly, we identify the characteristics of four network parameters in the ten most frequently studied disease genes and identify several specific patterns of their topologies. Then, we confirm our findings in the other disease genes of three complex disorders (i.e., Alzheimer's disease, diabetes mellitus, and hepatocellular carcinoma). The results reveal that the disease genes tend to have a higher betweenness centrality, a smaller average shortest path length, and a smaller clustering coefficient when compared to normal genes, whereas they have no significant degree prominence. The features highlight the importance of gene location in the integrated functional linkages.

Indexed as

Systems BiologyAlzheimer DiseaseCarcinoma, HepatocellularDiabetes MellitusGenetic LinkageHumansMetabolic Networks and Pathwaysdisease genelocation in networknetwork topological parametersystems biology

Identifiers

PMID30769902
PMCPMC6409865

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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.