RNA

An Efficient Approach based on Multi-sources Information to Predict CircRNA-disease Associations Using Deep Convoltional Neural Network

11 days ago   |   By Oxford Journals

AbstractMotivationEmerging evidence indicates that circular RNA plays a crucial role in human disease. Using circRNA as biomarker gives rise to a new perspective regarding our diagnosing of diseases and understanding of disease pathogenesis. However, detection of circRNA-disease associations by biological experiments alone is often blind, limited to small-scale, high-cost and time-consuming. Therefore, there is an urgent need for reliable computational methods to rapidly infer the potential circRNA-disease associations on a large scale and to provide the most promising candidates for...
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MiR-409-3p is reduced in plasma and islet immune infiltrates of NOD diabetic mice and is differentially expressed in people with type 1 diabetes

11 days ago   |   By Springer

Abstract
Aims/hypothesis
MicroRNAs are a novel class of potential biomarkers emerging in many diseases, including type 1 diabetes. Here, we aim to analyse a panel of circulating miRNAs in non-obese diabetic mice and individuals with type 1 diabetes.
Methods
We adopted standardised methodologies for extracting miRNAs from small sample volumes to evaluate a profiling panel of mature miRNAs in paired plasma and laser-captured microdissected immune-infiltrated islets of recently diabetic and normoglycaemic NOD mice. Moreover, we validated the findings during disease progression and remission...
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An improved random forest-based computational model for predicting novel miRNA-disease associations

12 days ago   |   By Springer

Abstract
Background
A large body of evidence shows that miRNA regulates the expression of its target genes at post-transcriptional level and the dysregulation of miRNA is related to many complex human diseases. Accurately discovering disease-related miRNAs is conductive to the exploring of the pathogenesis and treatment of diseases. However, because of the limitation of time-consuming and expensive experimental methods, predicting miRNA-disease associations by computational models has become a more economical and effective mean.
Results
Inspired by the work of predecessors, we proposed an...
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A novel target convergence set based random walk with restart for prediction of potential LncRNA-disease associations

12 days ago   |   By Springer

Abstract
Background
In recent years, lncRNAs have been proved to be closely related to the occurrence and development of many serious diseases that are seriously harmful to human health. However, most of the lncRNA-disease associations have not been found yet due to high costs and time complexity of traditional bio-experiments. Hence, it is quite urgent and necessary to establish efficient and reasonable computational models to predict potential associations between lncRNAs and diseases.
Results
In this manuscript, a novel prediction model called TCSRWRLD is proposed to predict potential...
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