PDS Releases First Publicly Available, FDA-Validated Dataset for SEND

Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have been studied using single cell RNA-sequencing (scRNA-seq). This finding could help researchers identify new cell subtypes and differentiate between healthy and diseased cells.

NIMS and the Toyota Technological Institute at Chicago have jointly developed a Computer-Aided Material Design (CAMaD) system that enables information from thousands of scientific and technical articles to be summarized in a single chart, rationalizing and expediting material design.

Large-scale supercomputing is essential to solving complex questions about our world. But storage platforms essential for these advanced computer systems have been stuck in a rigid framework that required users to either choose between customization of features or high availability. Now, researchers have found a way to give high-performance computing data systems the flexibility to thrive with a framework called BespoKV, perhaps helping to one day achieve the HPC goal of performing at the exascale, or 1 billion billion calculations per second.