Abstract
MiRNAs are a family of small, endogenous, and evolutionarily conserved non-coding ribonucleic acids that have been involved in the regulation of several essential, cellular, and functional processes. MicroRNAs are known to play key roles in all types of cancer and function as oncogenes (oncomirs) or tumour-suppressors in up-regulation or down-regulation processes respectively. MiRNAs have potential power to be examined as prognostic and diagnostic biomarkers. Modulating miRNAs, based on two major approaches (miRNA mimics and miRNA antagonists), is used for clinical development of therapeutic miRNAs. This review emphasizes the latest discovery in the field of miRNA research involved in cancer, biomarkers, and therapeutics.
Keywords: Biomarkers, cancer, microRNAs, therapeutics.
Call for Papers in Thematic Issues
Artificial Intelligence in Bioinformatics
Bioinformatics is an interdisciplinary field that analyzes and explores biological data. This field combines biology and information system. Artificial Intelligence (AI) has attracted great attention as it tries to replicate human intelligence. It has become common technology for analyzing and solving complex data and problems and encompasses sub-fields of machine ...read more
Latest Advancements in Biotherapeutics.
The scope of this thematic issue is to comprehensively explore the rapidly evolving landscape of biotherapeutics, emphasizing breakthroughs in precision medicine. Encompassing diverse therapeutic modalities, the issue will delve into the latest developments in monoclonal antibodies, CRISPR/Cas gene editing, CAR-T cell therapies, and innovative drug delivery systems, such as nanoparticle-based ...read more
Machine Learning and Artificial Intelligence for Medical Data Analysis and Human Information Analysis in Healthcare
The intersection of machine learning (ML) and artificial intelligence (AI) with the pharmaceutical industry is revolutionizing traditional paradigms in drug discovery and development. These technologies have introduced innovative approaches to analyzing complex datasets and predicting chemical properties, leading to more efficient identification and optimization of drug candidates. By employing sophisticated ...read more
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