Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)
☆19Jun 15, 2025Updated 8 months ago
Alternatives and similar repositories for graphVCI
Users that are interested in graphVCI are comparing it to the libraries listed below
Sorting:
- Counterfactual Generative Modeling with Variational Causal Inference (ICLR 2025)☆20Sep 30, 2025Updated 5 months ago
- A Unified RNA Sequencing Model (URSM) for joint analysis of single cell and bulk RNA-seq data.☆11Oct 20, 2017Updated 8 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆135Aug 14, 2024Updated last year
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆337Feb 1, 2025Updated last year
- ☆12Aug 19, 2025Updated 6 months ago
- code for paper: Identifiability Guarantees for Causal Disentanglement from Soft Interventions☆15Nov 27, 2023Updated 2 years ago
- Software for data-independent acquisition (DIA) proteomic data processing with deep representation features.☆14Sep 19, 2025Updated 5 months ago
- ☆33Oct 4, 2020Updated 5 years ago
- GrandPrix☆16May 27, 2019Updated 6 years ago
- ☆19Jun 23, 2023Updated 2 years ago
- Factorize-Recover for Perturb-seq analysis (FR-Perturb)☆25Nov 4, 2025Updated 4 months ago
- ☆20Mar 16, 2019Updated 6 years ago
- ☆25Oct 14, 2024Updated last year
- ☆72Jul 18, 2025Updated 7 months ago
- Git Repo for simulating Boolean Models☆37Nov 7, 2025Updated 3 months ago
- Single-cell perturbation effects prediction benchmark☆66Jan 6, 2026Updated last month
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell lev…☆184Sep 7, 2023Updated 2 years ago
- Single-Cell (Perturbation) Model Library☆92Jan 17, 2026Updated last month
- ☆11Feb 2, 2026Updated last month
- Tools for sgRNA calling in direct capture Perturb-seq data☆41Jun 18, 2023Updated 2 years ago
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆159Oct 31, 2024Updated last year
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆169Feb 25, 2025Updated last year
- Deep learning for identifying cis-regulatory elements and other applications☆34Nov 21, 2016Updated 9 years ago
- A benchmark on predicting how small molecules change gene expression in different cell types.☆15Jul 4, 2025Updated 8 months ago
- ☆10Oct 18, 2021Updated 4 years ago
- ☆14Apr 7, 2025Updated 10 months ago
- ☆15Dec 18, 2024Updated last year
- Basics of the OSCA book☆14Sep 29, 2025Updated 5 months ago
- This tool designs guides for use with the base editor technology.☆12Aug 11, 2023Updated 2 years ago
- Variational Auto Encoders for learning binding signatures of transcription factors☆14Mar 14, 2024Updated last year
- A Generative Adversarial Network Model Alternative to Animal Studies for Clinical Pathology Assessment☆14Jan 10, 2024Updated 2 years ago
- Implementation of gene-level rare coding variant association tests targeting allelic series: cases where increasingly deleterious mutatio…☆14Oct 22, 2025Updated 4 months ago
- Calculate DNA methylation age using Horvath 2013 method☆11Aug 25, 2017Updated 8 years ago
- Sequential Optimal Experimental Design of Perturbation Screens Guided by Multimodal Priors☆43May 25, 2024Updated last year
- Volumetric extensions to Torch's modules☆10Jul 25, 2017Updated 8 years ago
- Just a demonstration of some sampling techniques (rejection sampling, importance sampling, sampling importance resampling, Metropolis sam…☆11Aug 24, 2013Updated 12 years ago
- Deep Learning For Biological Sequence Data: From Convolutional Neural Networks To Transformers, our tutorial into DL presented at 21st Eu…☆10Sep 20, 2022Updated 3 years ago
- Analysis code for the TAP-seq manuscript.☆11Jun 25, 2021Updated 4 years ago
- Code for Paper Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning☆13Aug 11, 2022Updated 3 years ago