openproblems-bio / neurips2021_multimodal_topmethods
☆75Updated 3 years ago
Alternatives and similar repositories for neurips2021_multimodal_topmethods
Users that are interested in neurips2021_multimodal_topmethods are comparing it to the libraries listed below
Sorting:
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆50Updated 3 years ago
- ☆18Updated 3 years ago
- ☆17Updated 3 years ago
- This repository implements Graph Variational Causal Inference (graphVCI), a framework that integrates prior knowledge of relational infor…☆18Updated 2 months ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 3 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆56Updated 3 years ago
- Single-Cell Multimodal Prediction via Transformer☆27Updated last year
- ☆79Updated last year
- ☆29Updated 3 years ago
- ☆61Updated last year
- a unified single-cell data integration framework by optimal transport☆35Updated 7 months ago
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆19Updated 10 months ago
- CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis☆33Updated 2 years ago
- Single cell joint embedding and modality prediction with autoencoder☆9Updated 2 years ago
- ☆20Updated 7 months ago
- ☆38Updated 2 years ago
- Single-cell biological network inference using a heterogeneous graph transformer☆72Updated 2 months ago
- CoGO: a contrastive learning framework to predict disease similarity based on gene network and ontology structure☆16Updated 7 months ago
- An unsupervised scRNA-seq analysis workflow with graph attention networks☆23Updated 2 years ago
- CellBox: Interpretable Machine Learning for Perturbation Biology☆54Updated last year
- single-cell graph autoencoder☆22Updated 3 years ago
- covolutional neural network based coexpression analysis☆77Updated 4 years ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆112Updated 3 months ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆32Updated 2 weeks ago
- Codes for paper: Evaluating the Utilities of Large Language Models in Single-cell Data Analysis.☆69Updated 4 months ago
- Git Repo for simulating Boolean Models☆34Updated 11 months ago
- Batch-adversarial variational auto-encoder (BAVARIA) for simultaneous dimensionality reduction and integration of single-cell ATAC-seq da…☆14Updated 2 years ago
- scDeepCluster for Single Cell RNA-seq data☆101Updated 10 months ago
- Models and datasets for perturbational single-cell omics☆154Updated 2 years ago
- ☆13Updated 3 weeks ago