This comprehensive review explores the pivotal role of ensemble machine learning
techniques in Quantitative Structure-Activity Relationship (QSAR) modeling for drug …

The liver is a key organ involved in a wide range of functions, whose damage can lead to
chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide …

Computational drug repurposing is an efficient method to utilize existing knowledge for
understanding and predicting their effect on neurological diseases. The ability of a molecule …

Biofilms are one of the leading causes of antibiotic resistance. It acts as a physical barrier
against the human immune system and drugs. The use of anti-biofilm agents helps in …

Dengue outbreaks persist in global tropical regions, lacking approved antivirals,
necessitating critical therapeutic development against the virus. In this context, we …

Background Rhodopsin is a seven-transmembrane protein covalently linked with retinal
chromophore that absorbs photons for energy conversion and intracellular signaling in …

Machine learning (ML) is revolutionizing drug repurposing, offering a more efficient, cost‐
effective approach to drug discovery by identifying new therapeutic uses for existing drugs …

Hepatitis C virus (HCV) infection has become a serious concern because it can trigger the
severity of complications leading to hepatocellular carcinoma (HCC). HCV is a virus with …

The quantitative structure activity relationship (QSAR) study was carried out to predict the
anti-breast cancer effect of 2-Aminothiazole derivatives. heuristic method (HM), random …

Hepatitis is one of the dangerous diseases that result from viral infections. This virus attacks
the liver leading to its inflammation. Inflammation may lead to the death of the liver cells and …