ArticleScientific reports2012
Identification of links between small molecules and miRNAs in human cancers based on transcriptional responses.
Article in Scientific reports, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed, 75 citations in OpenAlex.
- MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks.BMC bioinformatics · 2025Article
- Drug Repurposing: Insights into Current Advances and Future Applications.Current medicinal chemistry · 2025Review
- MicroRNA Guided In Silico Drug Repositioning for Malaria.Acta parasitologica · 2024Article
- Small molecules targeting microRNAs: new opportunities and challenges in precision cancer therapy.Trends in cancer · 2024Review
- Article
- Review
- Combining non-negative matrix factorization with graph Laplacian regularization for predicting drug-miRNA associations based on multi-source information fusion.Frontiers in pharmacology · 2023Article
- Drug Repositioning Based on the Enhanced Message Passing and Hypergraph Convolutional Networks.Biomolecules · 2022Article
- PSRR: A Web Server for Predicting the Regulation of miRNAs Expression by Small Molecules.Frontiers in molecular biosciences · 2022Article
- Prediction of potential small molecule-miRNA associations based on heterogeneous network representation learning.Frontiers in genetics · 2022Article
- Identification of miRNA-Small Molecule Associations by Continuous Feature Representation Using Auto-Encoders.Pharmaceutics · 2021Article
- Noncoding RNA therapeutics - challenges and potential solutions.Nature reviews. Drug discovery · 2021Review
- A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions.Journal of cheminformatics · 2020Review
- SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association.RNA biology · 2020Article
- Prediction of Potential Associations Between miRNAs and Diseases Based on Matrix Decomposition.Frontiers in genetics · 2020Article
- Identifying Small Molecule-miRNA Associations Based on Credible Negative Sample Selection and Random Walk.Frontiers in bioengineering and biotechnology · 2020Article
- Identification and profiling of microRNAs expressed in oral buccal mucosa squamous cell carcinoma of Chinese hamster.Scientific reports · 2019Article
- Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks.Scientific reports · 2019Article
- In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm.Molecular therapy. Nucleic acids · 2019Article
- Inferring microRNA-Environmental Factor Interactions Based on Multiple Biological Information Fusion.Molecules (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of small molecules to target miRNAs is a new type of therapy for human diseases, particularly cancers. We proposed a novel high-throughput approach to identify the biological links between small molecules and miRNAs in 23 different cancers and constructed the Small Molecule-MiRNA Network (SMirN) for each cancer to systematically analyze the properties of their associations. In each SMirN, we partitioned small molecules (miRNAs) into modules, in which small molecules (miRNAs) were connected with one miRNA (small molecule). Almost all of the miRNA modules comprised miRNAs that had similar target genes and functions or were members of the same miRNA family. Most of the small molecule modules involved compounds with similar chemical structures, modes of action, or drug interactions. These modules can be used to identify drug candidates and new indications for existing drugs. Therefore, our approach is valuable to drug discovery and cancer therapy.
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Registered trials
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.