Advancing miRNA cancer research through artificial intelligence: from biomarker discovery to therapeutic targeting.

MicroRNAs (miRNAs), a class of small non-coding RNAs, play a vital role in regulating gene expression at the post-transcriptional level. Their discovery has profoundly impacted therapeutic strategies, particularly in cancer treatment, where RNA therapeutics, including miRNA-based targeted therapies, have gained prominence. Advances in RNA sequencing technologies have facilitated a comprehensive exploration of miRNAs-from fundamental research to their diagnostic and prognostic potential in various diseases, notably cancers.

Identification of potential probiotics from fermented sour traditional rice varieties and simulation studies.

Fermented products contain probiotic organisms that have beneficial and therapeutic effects on the gastrointestinal tract. The main objective of the study is to isolate probiotic bacteria from fermented sour traditional rice water and to evaluate their probiotic activity. The microbes were isolated from the fermented rice water and the characterization of the organisms was determined using MALDI-TOF MS.

A Review on Deep Learning-driven Drug Discovery: Strategies, Tools and Applications.

It takes an average of 10-15 years to uncover and develop a new drug, and the process is incredibly time-consuming, expensive, difficult, and ineffective. In recent years the dramatic changes in the field of artificial intelligence (AI) have helped to overcome the challenges in the drug discovery pipeline. Artificial intelligence (AI) has taken root in various pharmaceutical sectors, from lead compound identification to clinical trials.

Integrative transcriptome analysis of triple negative breast cancer profiles for identification of druggable targets.

As triple negative breast cancer (TNBC) lacks a specific target, exploration of abnormally expressed genes during the progression of TNBC is important for a better understanding of tumorigenesis and to find a specific target. We intended to figure out genes associated with TNBC, which can provide unique insights into gene dysregulation in TNBC while also pointing to new possible therapeutic targets for TNBC. A meta-analysis of multiple TNBC mRNA profiles was performed to identify consistently differentially expressed genes (CDGs).