Evidence map›Paper›PMID 26538106›Full record

ArticleBMC bioinformatics2015

Inferring plant microRNA functional similarity using a weighted protein-protein interaction network.

Jun Meng, Dong Liu, Yushi Luan

Abstract read
In one paragraph

Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jun MengSchool of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China. mengjun@dlut.edu.cn.
Dong LiuSchool of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China. kobe_liudong@mail.dlut.edu.cn.
Yushi LuanSchool of Life Science and Biotechnology, Dalian University of Technology, Dalian, Liaoning, China. luanyush@dlut.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMiRNAs play a critical role in the response of plants to abiotic and biotic stress. However, the functions of most plant miRNAs remain unknown. Inferring these functions from miRNA functional similarity would thus be useful. This study proposes a new method, called PPImiRFS, for inferring miRNA functional similarity.

resultsThe functional similarity of miRNAs was inferred from the functional similarity of their target gene sets. A protein-protein interaction network with semantic similarity weights of edges generated using Gene Ontology terms was constructed to infer the functional similarity between two target genes that belong to two different miRNAs, and the score for functional similarity was calculated using the weighted shortest path for the two target genes through the whole network. The experimental results showed that the proposed method was more effective and reliable than previous methods (miRFunSim and GOSemSim) applied to Arabidopsis thaliana. Additionally, miRNAs responding to the same type of stress had higher functional similarity than miRNAs responding to different types of stress.

conclusionsFor the first time, a protein-protein interaction network with semantic similarity weights generated using Gene Ontology terms was employed to calculate the functional similarity of plant miRNAs. A novel method based on calculating the weighted shortest path between two target genes was introduced.

Indexed as

Protein Interaction MapsArabidopsisGenes, PlantMicroRNAsROC CurveSodium ChlorideSoftwareStress, PhysiologicalMicroRNAsSodium Chloride

Identifiers

PMID26538106
PMCPMC4634583

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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.