Frontiers

Inferred global dense residue transition graphs from primary structure sequences enable protein interaction prediction via directed graph convolutional neural networks

Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct ...
SiliconANGLE

Microsoft expands Fabric with LinkedIn-based graph engine, real-time maps

Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping capabilities, saying the enhancements enhance Fabric’s capacity to power ...
ZDNet

Graph databases are exploding, thanks to the AI boom - here's why

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Best laptop cooling pads Best flip ...
Newsweek

Graph Shows US Births Decline Over 50 Years

Prefer Newsweek on Google to see more of our trusted coverage when you search. Newsweek has created a graph to show how births in the United States have declined over the last 50 years. This has ...
IEEE

Prescribed-Time Nash Equilibrium Seeking for Pursuit-Evasion Game Under Intermittent Control With Undirected/Directed Graph

Abstract: This paper studies the prescribed-time Nash equilibrium (PTNE) seeking problem of the pursuit-evasion game (PEG) with second-order dynamics under the intermittent control (IC) strategy. To ...
IEEE

Vertex-Frequency Analysis on Directed Graphs

Abstract: Vertex-frequency analysis (VFA) is a useful technique in graph signal processing to extract the correspondence between frequencies and vertices. VFA can be calculated by the windowed graph ...
Frontiers

Both k-core percolation and directed graph analysis revealed succession and transition of voxels’ spatiotemporal progress on dynamic correlation resting-state fMRI

Directed graphs and their afferent/efferent capacities are produced by Markov modeling of the universal cover of undirected graphs simultaneously with the calculation of volume entropy. Using these ...
marktechpost

Neural SpaceTimes (NSTs): A Class of Trainable Deep Learning-based Geometries that can Universally Represent Nodes in Weighted Directed Acyclic Graphs (DAGs) as Events in a ...

Directed graphs are crucial in modeling complex real-world systems, from gene regulatory networks and flow networks to stochastic processes and graph metanetworks. Representing these directed graphs ...