Cell-type Assignment and Module Extraction based on a heterogeneous graph neural network.
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Updated
Jan 27, 2024 - Python
Cell-type Assignment and Module Extraction based on a heterogeneous graph neural network.
Code for "Whole brain alignment of spatial transcriptomics between humans and mice with BrainAlign"
Code to reproduce Adaptive elastic-net sparse PCA for robust cross-species, cross-platform analysis of complex gene expression data in Alzheimer’s disease (Hin et al.)
Workflow to identify functional cis-regulatory regions for each annotated cell type
Scan genomes for internally repeated sequences, elements which are repetitive in another species, or high-identity HGT candidate regions between species.
Cross-species integration of single cell RNA-seq data from the primary motor cortex between human, mouse and drosophila using expiMap and SATURN
A gene regulation model reveals an ancestral adaptation response to particulate exposure triggered by nanomaterials
Incorporating Triplet Error for Predicting PPIs using Deep Learning
This is the lesson repository for the Workshop on Computational Techniques and Resources for Effective Translational Research in Alzheimer's Disease.
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