A collaborative research team led by Professor Pan Feng from the School of New Materials at Peking University Shenzhen ...

A newly developed physics-informed variational autoencoder (P-VAE) framework could help speed up computational imaging by using supervised learning to jointly reconstruct many light sources, each ...

Various candidates are limited by actual sequencing data from an experiment. Here we developed RaptGen, which is a variational autoencoder for in silico aptamer generation,” write the investigators.

In the not-so-distant past, researchers had to pool thousands of cells together for bulk RNA sequencing, yielding an averaged snapshot of gene expression. But advances in technology and significant ...

Computational methods used to fill in missing pixels in low-quality images or video also can help scientists provide missing information for how DNA is organized in the cell, computational ...