ArticleBMC bioinformatics2013
Using context-specific effect of miRNAs to identify functional associations between miRNAs and gene signatures.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed, 54 citations in OpenAlex.
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- Identification and validation of differentially expressed genes for targeted therapy in NSCLC using integrated bioinformatics analysis.Frontiers in oncology · 2023Article
- SMMDA: Predicting miRNA-Disease Associations by Incorporating Multiple Similarity Profiles and a Novel Disease Representation.Biology · 2022Article
- GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder.PLoS computational biology · 2021Article
- Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations.BMC bioinformatics · 2021Article
- Genome-scale meta-analysis of breast cancer datasets identifies promising targets for drug development.Journal of biological research (Thessalonike, Greece) · 2021Article
- ILPMDA: Predicting miRNA-Disease Association Based on Improved Label Propagation.Frontiers in genetics · 2021Article
- Biased Random Walk With Restart on Multilayer Heterogeneous Networks for MiRNA-Disease Association Prediction.Frontiers in genetics · 2021Article
- MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.BMC bioinformatics · 2020Article
- Systems-level differential gene expression analysis reveals new genetic variants of oral cancer.Scientific reports · 2020Article
- Predicting miRNA-disease association from heterogeneous information network with GraRep embedding model.Scientific reports · 2020Article
- Improved Prediction of miRNA-Disease Associations Based on Matrix Completion with Network Regularization.Cells · 2020Article
- Panel 2- recent advance in otitis media bioinformatics.International journal of pediatric otorhinolaryngology · 2020Review
- WBNPMD: weighted bipartite network projection for microRNA-disease association prediction.Journal of translational medicine · 2019Article
- Ensemble of decision tree reveals potential miRNA-disease associations.PLoS computational biology · 2019Article
- Dual Laplacian regularized matrix completion for microRNA-disease associations prediction.RNA biology · 2019Article
- PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach.BMC systems biology · 2019Article
- An integrated framework for the identification of potential miRNA-disease association based on novel negative samples extraction strategy.RNA biology · 2019Article
- Integrating random walk and binary regression to identify novel miRNA-disease association.BMC bioinformatics · 2019Article
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Authors and funding
2 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicroRNAs are a class of short regulatory RNAs that act as post-transcriptional fine-tune regulators of a large host of genes that play key roles in many cellular processes and signaling pathways. A useful step for understanding their functional role is characterizing their influence on the protein context of the targets. Using miRNA context-specific influence as a functional signature is promising to identify functional associations between miRNAs and other gene signatures, and thus advance our understanding of miRNA mode of action.
resultsIn the current study we utilized the power of regularized regression models to construct functional associations between gene signatures. Genes that are influenced by miRNAs directly(computational miRNA target prediction) or indirectly (protein partners of direct targets) are defined as functional miRNA gene signature. The combined direct and indirect miRNA influence is defined as context-specific effects of miRNAs, and is used to identify regulatory effects of miRNAs on curated gene signatures. Elastic-net regression was used to build functional associations between context-specific effect of miRNAs and other gene signatures (disease, pathway signatures) by identifying miRNAs whose targets are enriched in gene lists. As a proof of concept, elastic-net regression was applied on lists of genes downregulated upon pre-miRNA transfection, and successfully identified the treated miRNA. This model was then extended to construct functional relationships between miRNAs and disease and pathway gene lists. Integrating context-specific effects of miRNAs on a protein network reveals more significant miRNA enrichment in prostate gene signatures compared to miRNA direct targets. The model identified novel list of miRNAs that are associated with prostate clinical variables.
conclusionsElastic-net regression is used as a model to construct functional associations between miRNA signatures and other gene signatures. Defining miRNA context-specific functional gene signature by integrating the downstream effect of miRNAs demonstrates better performance compared to the miRNA signature alone (direct targets). miRNA functional signatures can greatly facilitate miRNA research to uncover new functional associations between miRNAs and diseases, drugs or pathways.
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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.