Mechanistic learning refers to the synergistic combination of mechanistic mathematical
modeling and data-driven machine or deep learning. This emerging field finds increasing …

Highlights•In silico prediction of drug combination has become indispensable due to the
expensive cost of experiments.•Deep learning architectures used for drug combination …

Cancer is one of the biggest medical challenges we face today. It is characterized by
abnormal, uncontrolled growth of cells that can spread to different parts of the body. Cancer …

Metastatic melanoma has a very poor prognosis. Statins, 3-hydroxy-3-methyl-glutaryl-
coenzyme A reductase (HMGCR) inhibitors, are cholesterol-lowering agents with a potential …

The removal of damaged mitochondrial components through a process called mitochondrial
autophagy (mitophagy) is essential for the proper function of the mitochondrial network …

Combination therapy is a promising strategy for the successful treatment of cancer. The
large number of possible combinations, however, mean that it is laborious and expensive to …

Glioblastoma (GBM), a common cancer of the central nervous system (CNS), is considered
incurable worldwide. The treatment of GBM varies from patient to patient, as conventional …

Recent advancements in deep learning (DL) have played a crucial role in aiding experts to
develop personalized healthcare services, particularly in drug response prediction (DRP) for …

Cancer therapy resistance still poses the biggest hurdle to cancer treatment. In everyday
clinical practice, oncologists face resistance to numerous cancer therapies, resulting in …

Purpose: To explore the expression patterns and clinical significance of minichromosome
maintenance (MCM) complex members in retinoblastoma (RB). Methods: Single-cell RNA …