Murali-group / BeelineLinks
BEELINE: evaluation of algorithms for gene regulatory network inference
☆197Updated last month
Alternatives and similar repositories for Beeline
Users that are interested in Beeline are comparing it to the libraries listed below
Sorting:
- Models and datasets for perturbational single-cell omics☆168Updated 3 years ago
- ☆86Updated 2 years ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆154Updated 9 months ago
- Single-cell perturbation analysis☆217Updated last week
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆119Updated last year
- GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations☆315Updated 10 months ago
- A simulator for single-cell expression data guided by gene regulatory networks☆69Updated last year
- Multi-omic single-cell optimal transport tools☆180Updated this week
- Additional code and analysis from the single-cell integration benchmarking project☆69Updated 2 years ago
- Mapping out the coarse-grained connectivity structures of complex manifolds.☆231Updated 5 years ago
- ☆62Updated 4 months ago
- Transformer for One-Stop Interpretable Cell-type Annotation☆146Updated last year
- ☆87Updated last year
- Comprehensive suite for evaluating perturbation prediction models☆110Updated 3 weeks ago
- Compendium of available lists of ligand-receptor pairs and surface-secreted protein interactions.☆145Updated 2 years ago
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆151Updated last year
- ☆145Updated last year
- A software package for analyzing snapshots of developmental processes☆151Updated 3 years ago
- ☆101Updated 2 years ago
- Reference mapping for single-cell genomics☆393Updated this week
- Accelerated, Python-only, single-cell integration benchmarking metrics☆79Updated this week
- Batch balanced KNN☆176Updated 2 years ago
- Benchmarking analysis of data integration tools☆395Updated 2 months ago
- SIMBA: SIngle-cell eMBedding Along with features☆64Updated last year
- Single-Cell (Perturbation) Model Library☆84Updated 3 months ago
- ☆31Updated 5 years ago
- Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network☆106Updated 2 years ago
- A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to repr…☆227Updated 5 months ago
- PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation☆57Updated 4 months ago
- Graph-linked unified embedding for single-cell multi-omics data integration☆438Updated 3 weeks ago