AIMC Topic: MicroRNAs

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miRNA-Based Feature Classifier Is Associated with Tumor Mutational Burden in Head and Neck Squamous Cell Carcinoma.

BioMed research international
Tumor mutation burden (TMB) is considered to be an independent genetic biomarker that can predict the tumor patient's response to immune checkpoint inhibitors (ICIs). Meanwhile, microRNA (miRNA) plays a key role in regulating the anticancer immune re...

Predicting MicroRNA Sequence Using CNN and LSTM Stacked in Seq2Seq Architecture.

IEEE/ACM transactions on computational biology and bioinformatics
CNN and LSTM have proven their ability in feature extraction and natural language processing, respectively. So, we tried to use their ability to process the language of RNAs, i.e., predicting sequence of microRNAs using the sequence of mRNA. The idea...

A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

Frontiers in endocrinology
MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone metabolic diseases. However, the regulatory roles of miRNAs in osteoporosis have not been systemati...

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...