zhangxiaoyu11 / OmiVAELinks
End-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.
☆34Updated 4 years ago
Alternatives and similar repositories for OmiVAE
Users that are interested in OmiVAE are comparing it to the libraries listed below
Sorting:
- MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in…☆171Updated 4 years ago
- Multi-task deep learning framework for multi-omics data analysis☆48Updated 3 years ago
- ☆16Updated 4 years ago
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆152Updated last year
- ☆44Updated 10 months ago
- Experimental evaluation and comparison of multi-omics data integration methods for cancer subtyping☆14Updated 4 years ago
- scDeepCluster for Single Cell RNA-seq data☆103Updated last year
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 4 years ago
- An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.☆159Updated 3 years ago
- An interpretable deep learning model for cancer classification using high-dimensional omics data☆16Updated 3 years ago
- scDCC: Single Cell Deep Constrained Clustering☆41Updated last year
- ☆17Updated last year
- HiGCN: a hierarchical graph convolution network for representation learning of gene expression data☆13Updated 4 years ago
- Code to reproduce results in Ravindra NG* & Sehanobish A* et al. 2020, "Disease State Prediction From Single-Cell Data Using Graph Attent…☆18Updated 5 years ago
- P-NET, Biologically informed deep neural network for prostate cancer classification and discovery☆161Updated 3 years ago
- single-cell graph autoencoder☆24Updated 4 years ago
- Cell clustering for spatial transcriptomics data with graph neural network☆63Updated 2 years ago
- a deep learning approach for integrative cancer subtyping of multi-omics data☆38Updated last year
- Code for Nature Scientific Reports 2020 paper: "Unsupervised generative and graph neural methods for modelling cell differentiation" by I…☆18Updated 5 years ago
- DCAP:Integrating multi-omics data with deep learning for predicting cancer prognosis☆21Updated 4 years ago
- Similarity network fusion in Python☆88Updated 5 years ago
- Disease subnetwork detection with explainable Graph Neural Networks☆25Updated last year
- ☆79Updated 3 years ago
- Deep soft K-means clustering with self-training for single cell RNA sequence data☆25Updated 5 years ago
- ☆20Updated 4 years ago
- CoGO: a contrastive learning framework to predict disease similarity based on gene network and ontology structure☆16Updated last year
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- a unified single-cell data integration framework by optimal transport☆35Updated last year
- SALMON: Survival Analysis Learning with Multi-Omics Neural Networks☆67Updated last year
- single-cell graph attentional clustering☆14Updated 3 years ago