Prediction of Potential MicroRNA–Disease Association Using Kernelized Bayesian Matrix Factorization

Toprak, Ahmet; DOĞAN, Esma ERYILMAZ

doi:10.1007/s12539-021-00469-w

Cited by 6 publications

(3 citation statements)

References 47 publications

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“…MicroRNAs (miRNAs) are small endogenous ncRNAs with the size of approximately 22 nt. 14 MiRNAs are implicated in the post-transcriptional moderation of the expression of genes in virtually all critical cellular processes. 15 Previous studies revealed that abnormal miRNAs are connected to the occurrence and evolution of multiple cancers.…”

Section: Introductionmentioning

confidence: 99%

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CircSEPT9 promotes breast cancer progression by regulating PTBP3 expression via sponging miR‐625‐5p

Shi,

Li,

Chen

et al. 2024

Thoracic Cancer

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BackgroundBreast cancer (BC) is a common malignancy which threatens the health of women. Circular RNAs (circRNAs) are critical factors in multiple cancers, including BC. The aim of this experiment was to investigate the molecular mechanisms of circRNA Septin 9 (circSEPT9) in the progression of BC.MethodsCircSEPT9, microRNA‐625‐5p (miR‐625‐5p) and polypyrimidine tract‐binding protein 3 (PTBP3) levels were determined by quantitative real‐time polymerase chain reaction (qRT‐PCR). Western blot was performed to detect the protein levels of PTBP3, E‐cadherin and vimentin. Cell counting kit‐8 assay (CCK8) and thymidine analog 5‐ethynyl‐2′‐deoxyuridine (EDU) was utilized for proliferation examination. Flow cytometry was conducted to measure apoptosis. Transwell assay and wound healing assay to investigate the migration of BC cells. Glucose uptake and lactate production were determined by specific kits. Additionally, dual‐luciferase reporter assay and RNA immunoprecipitation (RIP) assay were utilized to verify the interaction. A murine xenograft model was established to investigate the function of circSEPT9 in BC in vivo.ResultsOverexpression of circSEPT9 was found in BC tissues and cells. Silencing circSEPT9 impeded BC cell proliferation, migration, epithelial–mesenchymal transition (EMT) and glycolytic metabolism but facilitated cell apoptosis in vitro. Meanwhile, circSEPT9 knockdown constrained tumor growth in vivo. MiR‐625‐5p was targeted by circSEPT9. The influence of silencing circSEPT9 on BC cell function was regained by miR‐625‐5p inhibitor. Furthermore, miR‐625‐5p regulated BC cell malignant phenotypes via downregulating PTBP3.ConclusioncircSEPT9 contributed to the malignant progression of BC by up‐regulating PTBP3 via sponging miR‐625‐5p.

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Section: Introductionmentioning

confidence: 99%

“…MicroRNAs (miRNAs) are small endogenous ncRNAs with the size of approximately 22 nt 14 . MiRNAs are implicated in the post‐transcriptional moderation of the expression of genes in virtually all critical cellular processes 15 .…”

Section: Introductionmentioning

confidence: 99%

CircSEPT9 promotes breast cancer progression by regulating PTBP3 expression via sponging miR‐625‐5p

Shi,

Li,

Chen

et al. 2024

Thoracic Cancer

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“…Researchers have developed many computational methods to predict disease-associated miRNAs, lncRNAs, circRNAs, microbes, and environmental factor. For example, Toprak et al (Toprak & Eryilmaz Dogan, 2021; used two different methods for miRNA-disease associations prediction: KBMF and "weighted k-nearest known neighbors and network consistency projection". The ILDMSF method for prediction of lncRNA-disease associations was developed by Chen et al (Q. Chen et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for miRNA-Disease Association Prediction based on Space Projection and Label Propagation (SPLPMDA)

Toprak

2022

IJERAD

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miRNAs, a subclass of non-coding small RNAs, are about 18-22 nucleotides long. It has been revealed that miRNAs are responsible many diseases such as cancer. Therefore, great efforts have been made recently by researchers to explore possible relationships between miRNAs and diseases. Experimental studies to identify new disease-associated miRNAs are very expensive and at the same time a long process. Therefore, to determine the relationships between miRNA and disease many computational methods have been developed. In this paper, a new method for the identification of miRNA-disease associations based on space projection and label propagation (SPLPMDA) is proposed. The forecast the precision of SPLPMDA was demonstrated using 5-fold cross-validation and LOOCV techniques. Values of 0.9333 in 5-fold cross validation and 0.9441 in LOOCV were obtained. Moreover, case studies on breast neoplasms and lymphoma were performed to further confirm the predictive reliability of SPLPMDA.

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PmliHFM: Predicting Plant miRNA-lncRNA Interactions with Hybrid Feature Mining Network

Chen

Sun

2022

Interdiscip Sci Comput Life Sci

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Prediction of Potential MicroRNA–Disease Association Using Kernelized Bayesian Matrix Factorization

Cited by 6 publications

References 47 publications

CircSEPT9 promotes breast cancer progression by regulating PTBP3 expression via sponging miR‐625‐5p

CircSEPT9 promotes breast cancer progression by regulating PTBP3 expression via sponging miR‐625‐5p

A Novel Method for miRNA-Disease Association Prediction based on Space Projection and Label Propagation (SPLPMDA)

PmliHFM: Predicting Plant miRNA-lncRNA Interactions with Hybrid Feature Mining Network

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