IEEE

GraNDe: Near-Data Processing Architecture With Adaptive Matrix Mapping for Graph Convolutional Networks

Abstract: Graph Convolutional Network (GCN) models have attracted attention given their high accuracy in interpreting graph data. One of the primary building blocks of a GCN model is aggregation, ...
IEEE

sigRGCN: A Robust Residual Graph Convolutional Network for scRNA-Seq Data Clustering

Abstract: Clustering is a crucial step in single-cell RNA sequencing (scRNA-seq) data analysis, facilitating the discovery of new cell types and the grouping of similar cells. Recently, graph ...
University of Wyoming

Dice Roll Bar Graph

This module uses random number generators to simulate dice rolls. The user can provide any number of different sided dice and the number of times the dice are rolled. The program will then produce a ...
GitHub

Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network

The inference of cell-cell communication (CCC) is crucial for a better understanding of complex cellular behavior and regulatory mechanisms in biological systems. However, current computational ...