Deep learning with Convolutional Neural Networks has shown great promise in image-based
classification and enhancement but is often unsuitable for predictive modeling using …

Drug sensitivity prediction for individual tumors is a significant challenge in personalized
medicine. Current modeling approaches consider prediction of a single metric of the drug …

Background In precision medicine, scarcity of suitable biological data often hinders the design
of an appropriate predictive model. In this regard, large scale pharmacogenomics studies, …

Tailoring optimal treatment for individual cancer patients remains a significant challenge. To
address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression-…

Ammonia is a cytotoxic molecule generated during normal cellular functions. Dysregulated
ammonia metabolism, which is evident in many chronic diseases such as liver cirrhosis, heart …

The ability to estimate the force field parameters of materials is critical for calculating the
properties of materials using molecular dynamics (MD) simulations. The density functional …

Recent years have seen an increase in the availability of pharmacogenomic databases such
as Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (…

Emerging applications of radio frequency (RF) vision sensors for security and gesture recognition
primarily target single individual scenarios which restricts potential applications. In this …

Background Clinical studies often track dose-response curves of subjects over time. One
can easily model the dose-response curve at each time point with Hill equation, but such a …

Deep learning with Convolutional Neural Networks has shown great promise in various
areas of image-based classification and enhancement but is often unsuitable for predictive …