A new, densely annotated 3D-text dataset called 3D-GRAND can help train embodied AI, like household robots, to connect ...

"Reconstructing 3D chromosome structures from single-cell Hi-C data with SO(3)-equivariant graph neural networks," was published in NAR Genomics and Bioinformatics. More information: Yanli Wang et ...

We present a graph-based computational ... clusters in tens of thousands of 3D genome structures. Integrating epigenomics and functional genomics data, we show that the clusters are involved ...

Engineers at the UCLA Samueli School of Engineering have introduced a universal framework for point spread function (PSF) engineering, enabling the synthesis of arbitrary, spatially varying 3D PSFs ...

However, the complexity of data is often significant, especially when the scanned object has internal 3D structures, like rough edges. Edge-highlighting visualization is a technique used to ...

From our part, let's try to approach the analytics progression from a different viewpoint, focusing on a specific data structure: graphs. What is the optimal way to go through a number of bridges?

“Reconstructing 3D chromosome structures from single-cell Hi-C data with SO(3)-equivariant graph neural networks,” was published in NAR Genomics and Bioinformatics.