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MicroRNAs

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LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions.

Computational biology and chemistry
The interactions between miRNAs and long non-coding RNAs (lncRNAs) are subject to intensive recent studies due to its critical role in gene regulations. Computational prediction of lncRNA-miRNA interactions has become a popular alternative strategy t...

Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME.

F1000Research
In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over time and several researchers ...

Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis.

BMC medical informatics and decision making
BACKGROUND: Breast cancer is the most prevalent and among the most deadly cancers in females. Patients with breast cancer have highly variable survival lengths, indicating a need to identify prognostic biomarkers for personalized diagnosis and treatm...

A review of Cloud computing technologies for comprehensive microRNA analyses.

Computational biology and chemistry
Cloud computing revolutionized many fields that require ample computational power. Cloud platforms may also provide huge support for microRNA analysis mainly through disclosing scalable resources of different types. In Clouds, these resources are ava...

A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of surgery and consequently leads to a high mortality rate. Pivotal improvements in circulating microRNA e...

MicroRNA Profiling as a Methodology to Diagnose Ménière's Disease: Potential Application of Machine Learning.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Diagnosis and treatment of Ménière's disease remains a significant challenge because of our inability to understand what is occurring on a molecular level. MicroRNA (miRNA) perilymph profiling is a safe methodology and may serve as a "liqu...

PlantMirP-Rice: An Efficient Program for Rice Pre-miRNA Prediction.

Genes
Rice microRNAs (miRNAs) are important post-transcriptional regulation factors and play vital roles in many biological processes, such as growth, development, and stress resistance. Identification of these molecules is the basis of dissecting their re...

A novel graph attention adversarial network for predicting disease-related associations.

Methods (San Diego, Calif.)
Identifying complex human diseases at molecular level is very helpful, especially in diseases diagnosis, therapy, prognosis and monitoring. Accumulating evidences demonstrated that RNAs are playing important roles in identifying various complex human...

Prediction of miRNA targets by learning from interaction sequences.

PloS one
MicroRNAs (miRNAs) are involved in a diverse variety of biological processes through regulating the expression of target genes in the post-transcriptional level. So, it is of great importance to discover the targets of miRNAs in biological research. ...

Age estimation using bloodstain miRNAs based on massive parallel sequencing and machine learning: A pilot study.

Forensic science international. Genetics
Age estimation is one of the most important components in the practice of forensic science, especially for body fluids or stains at crime scenes. Recent studies have focused on the application of DNA methylation for chronological age determination in...