RaminHasibi / GraphFeatureAutoencoder
A repo for implementation of Graph features autoencoder for expression values prediction and imputation
☆17Updated 3 years ago
Related projects: ⓘ
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆55Updated 3 years ago
- single-cell graph autoencoder☆21Updated 2 years ago
- Interpretation by Deep Generative Masking for Biological Sequences☆34Updated 2 years ago
- Contextualizing protein representations using deep learning on protein networks and single-cell data☆67Updated last week
- Hypergraph Factorisation☆20Updated last year
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆24Updated last year
- scPretrain: Multi-task self-supervised learning for cell type classification☆21Updated 2 years ago
- A Python toolkit for setting up benchmarking dataset using biomedical networks☆20Updated last month
- Biological Network Integration using Convolutions☆58Updated 8 months ago
- Code for Nature Scientific Reports 2020 paper: "Unsupervised generative and graph neural methods for modelling cell differentiation" by I…☆17Updated 4 years ago
- ☆31Updated last year
- CellBox: Interpretable Machine Learning for Perturbation Biology☆54Updated last year
- ☆17Updated 3 years ago
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆18Updated 2 months ago
- Latent Diffusion Model for DNA Sequence Generation☆17Updated 4 months ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆48Updated 2 years ago
- A deep generative neural network based approach to impute drug response☆18Updated 3 years ago
- Single cell joint embedding and modality prediction with autoencoder☆9Updated 2 years ago
- ☆19Updated last year
- surrogate quantitative interpretability for deepnets☆16Updated 2 months ago
- ☆71Updated last year
- CoGO: a contrastive learning framework to predict disease similarity based on gene network and ontology structure☆16Updated 2 years ago
- Adversarial generation of gene expression data using Generative Adversarial Networks☆24Updated 2 years ago
- ☆36Updated last year
- Network-based project to explore gene connectivity through biological scales☆20Updated 2 years ago
- Transformer-based protein function Annotation with joint feature-Label Embedding☆31Updated last year
- ☆11Updated 2 years ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆28Updated last year
- a unified single-cell data integration framework by optimal transport☆30Updated last year
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆96Updated last month