Cell cycle associated miRNAs as target and therapeutics in lung cancer treatment.

Lung cancer is the primary cause of cancer related deaths worldwide. Limited therapeutic options and resistance to existing drugs are the major hindrances to the clinical success of this cancer. In the past decade, several studies showed the role of microRNA (miRNA) driven cell cycle regulation in lung cancer progression.

Computational epigenetic landscape analysis reveals association of CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1 lncRNAs in prostate cancer progression through aberrant methylation.

Aberrant expression of long non-coding RNAs (lncRNAs), caused by alterations in DNA methylation, is a driving factor in several cancers. Interplay between lncRNAs' aberrant methylation and expression in prostate cancer (PC) progression still remains largely elusive. Therefore, this study characterized the genome-wide epigenetic landscape and expression profiles of lncRNAs and their clinical impact by integrating multi-omics data implementing bioinformatics approaches.

Prospects for Protective Potential of against Kidney Diseases.

Kidney diseases are regarded as one of the major public health issues in the world. The objectives of this study were: (i) to investigate the causative factors involved in kidney disease and the therapeutic aspects of , as well as (ii) the effectiveness of in the anti-inflammation and antioxidant processes of the kidney while minimizing all potential side effects. In addition, we proposed a hypothesis to improve based drug development.

Genome-wide identification and prediction of SARS-CoV-2 mutations show an abundance of variants: Integrated study of bioinformatics and deep neural learning.

Genomic data analysis is a fundamental system for monitoring pathogen evolution and the outbreak of infectious diseases. Based on bioinformatics and deep learning, this study was designed to identify the genomic variability of SARS-CoV-2 worldwide and predict the impending mutation rate. Analysis of 259044 SARS-CoV-2 isolates identified 3334545 mutations with an average of 14.

Prediction of the Effects of Variants and Differential Expression of Key Host Genes , , and in SARS-CoV-2 Pathogenesis: An Approach.

A new strain of the beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is solely responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Although several studies suggest that the spike protein of this virus interacts with the cell surface receptor, angiotensin-converting enzyme 2 (ACE2), and is subsequently cleaved by TMPRSS2 and FURIN to enter into the host cell, conclusive insight about the interaction pattern of the variants of these proteins is still lacking. Thus, in this study, we analyzed the functional conjugation among the spike protein, ACE2, TMPRSS2, and FURIN in viral pathogenesis as well as the effects of the mutations of the proteins through the implementation of several bioinformatics approaches.

MicroRNAs expression analysis shows key affirmation of Synaptopodin-2 as a novel prognostic and therapeutic biomarker for colorectal and cervical cancers.

MicroRNAs play a crucial role in tumorigenesis, tumor progression, and metastasis, and thus they contribute in development of different malignancies including cervical cancer (CC) and colorectal cancer (CRC). Through integrated strategies of computational biology, this study aims to identify prognostic biomarkers responsible for CRC and CC prognosis, and potential therapeutic agents to halt the progression of these cancers. Expression analysis of miRNA datasets of CRC and CC identified 17 differentially expressed miRNAs (DEMs).