GitHub

scVAG: Unified Single-Cell Clustering via Variational-Autoencoder Integration with Graph Attention Autoencoder

scVAG is an innovative framework that integrates Variational Autoencoder (VAE) and Graph Attention Autoencoder (GATE) models for enhanced analysis of single-cell gene expression data. Built upon the ...
SciELO

The World of Cave Microbiomes: Biodiversity, Ecological Interactions, Chemistry, and the Multi-Omics Integration

Caves are ecosystems and natural heritage sites with magnificent biological diversity, from microorganisms to animals, despite their selective environment for development and survival. Until now, ...
IEEE

A Factor Graph-Based Multiple Sensors Fusion Method for Enhanced Underwater Navigation of Remotely Operated Vehicles

Abstract: The requirement for precision in underwater navigation has driven the development of advanced remotely operated vehicle (ROV) systems, necessitating the integration of multiple sensors to ...
IEEE

A Factor Graph Optimization-Based In-Motion Alignment Method for INS/DVL Integration

Abstract: An accurate initial attitude is of great importance for the integration of Doppler velocity log (DVL) and the strapdown inertial navigation system (SINS). The speed and accuracy of the ...
GitHub

Heterogeneous graph attention network improves cancer multiomics integration

The following shows an overview of the HeteroGATomics method. The source code, developed in Python 3.10, has been verified on both Linux and Windows and should be compatible with any operating system ...