☆34Oct 4, 2020Updated 5 years ago
Alternatives and similar repositories for scgen-reproducibility
Users that are interested in scgen-reproducibility are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Single cell perturbation prediction☆352Dec 5, 2024Updated last year
- Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)☆18Jun 15, 2025Updated last year
- Conditional out-of-distribution prediction☆64Aug 2, 2024Updated last year
- Notebooks for CPA figures☆15Dec 9, 2022Updated 3 years ago
- ☆14Jan 21, 2021Updated 5 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- ☆30Oct 14, 2024Updated last year
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆176Oct 31, 2024Updated last year
- Reproducing result from the paper☆34May 12, 2021Updated 5 years ago
- Clinical data for the TCGA PanCancer Atlas☆22Jul 12, 2019Updated 6 years ago
- ☆13Jun 4, 2023Updated 3 years ago
- [Cell Patterns] Codes for paper: scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis☆24Jan 31, 2026Updated 5 months ago
- Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.☆155Feb 6, 2025Updated last year
- Analysis of single cell RNA-Seq data from Veres et al.☆14Dec 10, 2019Updated 6 years ago
- Models and datasets for perturbational single-cell omics☆179Aug 19, 2022Updated 3 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆379Feb 1, 2025Updated last year
- scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism☆18Oct 17, 2024Updated last year
- ENHANCE: Accurate denoising of single-cell RNA-Seq data (Python implementation)☆15Jun 5, 2019Updated 7 years ago
- Single-cell RNA-seq Gene Expression Recovery☆116Nov 28, 2024Updated last year
- MEXPRESS is a data visualization tool designed for the visualization of TCGA expression, DNA methylation and clinical data.☆15Jul 23, 2020Updated 5 years ago
- Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data☆63Jul 22, 2024Updated last year
- ☆27Mar 31, 2026Updated 3 months ago
- Tensor Switching Networks☆12Nov 2, 2017Updated 8 years ago
- Run multiple Pipeline5 instances at once☆11Jun 6, 2025Updated last year
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- A computational method for comparing cellular profiles with the flexibility to place a higher weight on functional features of interest.☆12Jan 31, 2023Updated 3 years ago
- Population balance analysis☆46Apr 25, 2019Updated 7 years ago
- Multi-Layer Network Model leverages identification of spatial domains from spatial transcriptomics data☆13Aug 25, 2024Updated last year
- ☆21Nov 15, 2020Updated 5 years ago
- Tool for sharing, browsing and visualizing single-cell data stored in the Loom file format☆38Jan 10, 2025Updated last year
- ClusterMap is an R package to analyze and compare two or more single cell expression datasets.☆21Jan 17, 2023Updated 3 years ago
- Repository for the code for DeepATAC project presented at WCB workshop in ICML2017☆22Aug 9, 2017Updated 8 years ago
- Spatial reconstruction of dissociated single-cell data☆20Jan 12, 2024Updated 2 years ago
- Repository for the building, sharing and editing of scRNAseq pipelines for the Lung Cell Atlas☆41Jan 6, 2021Updated 5 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell lev…☆186Sep 7, 2023Updated 2 years ago
- ☆19Jul 8, 2021Updated 4 years ago
- Reference mapping for single-cell genomics☆406Jun 26, 2026Updated last week
- BEELINE: evaluation of algorithms for gene regulatory network inference☆210May 25, 2026Updated last month
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆148Aug 14, 2024Updated last year
- Scripts for data and figure generation in SAVER paper☆18Jan 5, 2021Updated 5 years ago
- ☆13Jul 18, 2025Updated 11 months ago