The rapid development of artificial intelligence (AI) technologies in the context of the vast
amount of collectable data obtained from high-throughput sequencing has led to an …

Network pharmacology can ascertain the therapeutic mechanism of drugs for treating
diseases at the level of biological targets and pathways. The effective mechanism study of …

Although drug combinations in cancer treatment appear to be a promising therapeutic
strategy with respect to monotherapy, it is arduous to discover new synergistic drug …

In silico design of single guide RNA (sgRNA) plays a critical role in clustered regularly
interspaced, short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) …

AI-enhanced virtual clinics and telemedicine are transforming cancer treatment by improving
access to care, diagnostic precision, and personalized treatment options. For patients …

Immune checkpoint inhibitors (ICIs) have heralded a new era in immunotherapy,
representing a pivotal breakthrough in cancer treatment. Their impact is profound, with ICIs …

Synergistic effects between drugs are rare and highly context-dependent and patient-
specific. Hence, there is a need to develop novel approaches to stratify patients for optimal …

Drug combination therapy is a highly effective approach for enhancing the therapeutic
efficacy of anti-cancer drugs and overcoming drug resistance. However, the innumerable …

Triple-negative breast cancer (TNBC) is a relatively aggressive breast cancer subtype due to
tumor relapse, drug resistance, and multi-organ metastatic properties. Identifying reliable …

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