☆53Jun 16, 2025Updated last year
Alternatives and similar repositories for perturblib
Users that are interested in perturblib are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Causal Differential Networks (ICML 2025)☆17Jun 3, 2025Updated last year
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆150Aug 14, 2024Updated 2 years ago
- ☆72Jan 14, 2026Updated 7 months ago
- A repository for reproducing experiments from the TxPert paper☆47Mar 25, 2026Updated 5 months ago
- ☆18Apr 23, 2026Updated 4 months 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.
- Single-cell perturbation analysis☆337Updated this week
- CellNavi is a deep learning framework designed to predict genes driving cellular transitions.☆55Jul 10, 2026Updated last month
- MaxToki: an autoregressive single-cell language model built on BioNeMo/NeMo/Megatron.☆28Jul 28, 2026Updated last month
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆66Jan 12, 2026Updated 7 months ago
- GenePert: Leveraging GenePT Embeddings for Gene Perturbation Prediction☆21Oct 29, 2024Updated last year
- Single-cell perturbation effects prediction benchmark☆103May 6, 2026Updated 3 months ago
- ☆96Aug 10, 2026Updated 3 weeks ago
- NeST-VNN repo☆12Jun 13, 2025Updated last year
- ☆15Jul 8, 2022Updated 4 years ago
- Open source password manager - Proton Pass • AdSecurely store, share, and autofill your credentials with Proton Pass, the end-to-end encrypted password manager trusted by millions.
- Nature Computational Science: Predicting drug responses of unseen cell types through transfer learning with foundation models☆42Feb 2, 2026Updated 7 months ago
- pytorch dataloaders for single-cell perturbation data☆51Jul 18, 2026Updated last month
- Contrastive pre-training for technology-agnostic single-cell representations beyond reconstruction☆38Aug 4, 2026Updated last month
- a dataloader to work with large single cell datasets from lamindb☆41Aug 27, 2026Updated last week
- State is a machine learning model that predicts cellular perturbation response across diverse contexts☆665Jul 24, 2026Updated last month
- ☆39Jun 8, 2026Updated 2 months ago
- BulkFormer: A large-scale foundation model for human bulk transcriptomes☆80Jul 3, 2026Updated 2 months ago
- PULSAR: a Foundation Model for Multi-scale and Multicellular Biology☆38Mar 1, 2026Updated 6 months ago
- ☆35Jun 11, 2026Updated 2 months ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆403Feb 1, 2025Updated last year
- ☆32Jan 22, 2025Updated last year
- Scripts for analysis of genome-wide perturb-seq in primary human T cells☆22Aug 28, 2026Updated last week
- AetherCell is a hierarchical generative framework designed to predict context-specific transcriptomic responses to drugs and genetic pert…☆20Jul 22, 2026Updated last month
- ☆184Jan 30, 2026Updated 7 months ago
- Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.☆41Jul 29, 2025Updated last year
- development of network co-localization tool☆18Mar 2, 2026Updated 6 months ago
- ☆34Aug 3, 2026Updated last month
- Code repository for TCAT analyses☆16Sep 26, 2025Updated 11 months ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Tahoe-x1 is a single cell foundation model designed for gigascale datasets☆163Aug 25, 2026Updated last week
- Unsupervised Deep Disentangled Representation of Single-Cell Omics☆80Updated this week
- Package to preprocess ontologies and train OntoVAE models.☆16Jan 7, 2025Updated last year
- Investigating the role of pre-training dataset size and diversity on the performance of single-cell foundation models☆21May 12, 2026Updated 3 months ago
- scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics☆52Jan 30, 2026Updated 7 months ago
- Modeling complex perturbations with CellFlow☆159Updated this week
- Network-based module discovery algorithm with high rate of empirically-validated term calls☆14Oct 22, 2023Updated 2 years ago