edianfranklin / autoencoder_for_cancer_subtype
☆11Updated 4 years ago
Alternatives and similar repositories for autoencoder_for_cancer_subtype:
Users that are interested in autoencoder_for_cancer_subtype are comparing it to the libraries listed below
- Multi-omics integration method using AE and GCN☆34Updated last year
- Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data☆54Updated 9 months ago
- Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence☆38Updated 2 years ago
- Cell clustering for spatial transcriptomics data with graph neural network☆61Updated 2 years ago
- ☆65Updated last year
- Iterative transfer learning with neural network improves clustering and cell type classification in single-cell RNA-seq analysis☆54Updated 3 years ago
- High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations☆48Updated 2 months ago
- Single-cell ATAC-seq analysis via Latent feature Extraction☆102Updated last year
- ☆42Updated last year
- ☆54Updated 2 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆49Updated 3 years ago
- Deep-Learning framework for multi-omic and survival data integration☆82Updated last year
- ☆100Updated 3 months ago
- Additional code and analysis from the single-cell integration benchmarking project☆60Updated 2 years ago
- ☆30Updated 2 years ago
- MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations☆76Updated 5 months ago
- Spatial Transcriptomic Analysis using Reference-Free auxiliarY deep generative modeling and Shared Histology☆115Updated 8 months ago
- Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space☆77Updated 3 weeks ago
- ☆17Updated 3 years ago
- Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network☆103Updated last year
- ☆90Updated 4 years ago
- Models and datasets for perturbational single-cell omics☆154Updated 2 years ago
- A benchmark of batch-effect correction methods for single-cell RNA sequencing data☆74Updated 3 years ago
- Deep Learning the T Cell Receptor Binding Specificity of Neoantigen☆80Updated 2 years ago
- ☆99Updated 2 years ago
- Compendium of available lists of ligand-receptor pairs and surface-secreted protein interactions.☆129Updated 2 years ago
- Reproducing the experiments of the DestVI paper☆18Updated 3 years ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆32Updated this week
- Single Cell Generative Adversarial Network (scGAN)☆14Updated 4 years ago
- Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data☆69Updated 3 months ago