Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …

Over the last decades, transcriptome profiling emerged as one of the most powerful
approaches in oncology, providing prognostic and predictive utility for cancer management …

Phenotype-based compound screening has advantages over target-based drug discovery,
but is unscalable and lacks understanding of mechanism of drug action. A chemical-induced …

Drug development is a time-consuming and expensive process, given the low success rate
of clinical trials. Now, anticancer drug developments have shifted to three-dimensional (3D) …

Simple Summary Colorectal cancer (CRC) is one of the most prevalent cancers worldwide.
Due to the absence of specific early symptoms, most of CRC patients are often diagnosed at …

Introduction: Cinnamomi ramulus (CR) is one of the most widely used traditional Chinese
medicine (TCM) with anti-cancer effects. Analyzing transcriptomic responses of different …

Chemical-induced gene expression profiles provide critical information of chemicals in a
biological system, thus offering new opportunities for drug discovery. Despite their success …

Dexamethasone, a synthetic glucocorticoid, has previously shown mortality benefit in severe
coronavirus disease 2019 (COVID-19) in a randomized controlled trial. As the illness is …

Matrix completion problems arise in many applications including recommendation systems,
computer vision, and genomics. Increasingly larger neural networks have been successful in …

One of the most challenging tasks in the drug-discovery process is the efficient identification
of small molecules with desired phenotypes. In this study, we propose a novel computational …