AIMC Topic: MicroRNAs

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Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.

PLoS computational biology
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Comp...

Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model.

Lipids in health and disease
BACKGROUND: Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving metabolic, inflammatory, and fibrogenic processes. Despite its burden, there has been a lack of any approved food-and-drug administration therapy up till ...

Exploration of the shared diagnostic genes and mechanisms between periodontitis and primary Sjögren's syndrome by integrated comprehensive bioinformatics analysis and machine learning.

International immunopharmacology
BACKGROUND: Accumulating evidence has showed a bidirectional link between periodontitis (PD) and primary Sjögren's syndrome (pSS), but the mechanisms of their occurrence remain unclear. Hence, this study aimed to investigate the shared diagnostic gen...

APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation.

Transplant immunology
BACKGROUND: Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stres...

Machine learning and bioinformatics analysis of diagnostic biomarkers associated with the occurrence and development of lung adenocarcinoma.

PeerJ
OBJECTIVE: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cancer-related deaths worldwide. This study is a review of three molecular biomarkers screened by machine learning that are not only important in the occur...

Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma.

Biochimica et biophysica acta. Molecular basis of disease
Osteosarcoma (OS), as the most common primary bone cancer, has a high invasiveness and metastatic potential, therefore, it has a poor prognosis. This study identified early diagnostic biomarkers using miRNA expression profiles associated with osteosa...

Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study.

Schizophrenia research
Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, del...

Machine Learning-Based Etiologic Subtyping of Ischemic Stroke Using Circulating Exosomal microRNAs.

International journal of molecular sciences
Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (E...

Dynamic Addressing Molecular Robot (DAMR): An Effective and Efficient Trial-and-Error Approach for the Analysis of Single Nucleotide Polymorphisms.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Accurate and efficient molecular recognition plays a crucial role in the fields of molecular detection and diagnostics. Conventional trial-and-error-based molecular recognition approaches have always been challenged in distinguishing minimal differen...