Bertinus / FLeCSLinks
Functional and Learnable Cell dynamicS
☆17Updated 4 months ago
Alternatives and similar repositories for FLeCS
Users that are interested in FLeCS are comparing it to the libraries listed below
Sorting:
- ☆37Updated 3 months ago
- ☆50Updated 2 months ago
- ☆63Updated 2 years ago
- ☆82Updated last year
- A simulator for single-cell expression data guided by gene regulatory networks☆63Updated last year
- Conditional out-of-distribution prediction☆63Updated last year
- SIMBA: SIngle-cell eMBedding Along with features☆63Updated 11 months ago
- Semi-supervised adversarial neural networks for classification of single cell transcriptomics data☆76Updated 8 months ago
- Models and datasets for perturbational single-cell omics☆163Updated 3 years ago
- spatial transcriptome, single cell☆69Updated 2 years ago
- Quantifying experimental perturbations at single cell resolution☆109Updated 11 months ago
- Template repository for creating novel models with scvi-tools☆20Updated 2 years ago
- ☆33Updated 5 months ago
- ☆36Updated this week
- CellBox: Interpretable Machine Learning for Perturbation Biology☆56Updated 2 years ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆46Updated 2 months ago
- Modeling complex perturbations with CellFlow☆85Updated this week
- Codebase for PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs) for generative modeling of single-cell time-series.☆49Updated 7 months ago
- Decima is a Python library to train sequence models on single-cell RNA-seq data.☆46Updated this week
- Spatial reconstruction of dissociated single-cell data☆19Updated last year
- ACTIONet single-cell analysis framework☆42Updated last year
- Unsupervised Deep Disentangled Representation of Single-Cell Omics☆48Updated this week
- ☆84Updated 2 years ago
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆53Updated 3 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆109Updated last year
- scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism☆15Updated 11 months ago
- code to run EPInformer for gene expression prediction and gene-enhancer links prioritization☆44Updated 9 months ago
- ☆15Updated 3 years ago
- Learning cell communication from spatial graphs of cells☆112Updated last year
- ☆59Updated last year