SCUBA
Cell differentiation model
A MATLAB package for modeling cell differentiation and lineage relationships from single-cell gene expression data.
11 stars
4 watching
9 forks
Language: MATLAB
last commit: about 3 years ago
Linked from 1 awesome list
Related projects:
| Repository | Description | Stars |
|---|---|---|
| | An algorithmic framework for inferring cell lineages from gene expression data through multiple rounds of downsampling and clustering, followed by consensus clustering and graph construction. | 1 |
| | Software to model transcriptional cell fates as mixtures of Gaussian Processes | 19 |
| | Software for inferring evolutionary lineage of tumor cells from single cell copy number profiles | 17 |
| | A curated metabolic model of Saccharomyces cerevisiae for systems biology and predictive modeling. | 97 |
| | A probabilistic model to analyze single-cell expression data during differentiation | 9 |
| | A climate model implementation using automatic differentiation and data assimilation to simulate global ocean circulation | 343 |
| | A package for visualizing single cell and spatial transcriptomics data using R | 43 |
| | Automated tool for classifying cells in scRNA data and inferring copy number profiles of malignant cells. | 94 |
| | A toolbox for incorporating enzyme constraints into genome-scale models of biological systems | 66 |
| | A toolset for analyzing single-cell gene expression data from RNA sequencing experiments. | 24 |
| | Analyzes 3D cell shape features using deep learning for cancer research | 21 |
| | Analyzing multiplexed single-cell RNA-seq data from a marine organism, providing tools for preprocessing, clustering, and analysis of gene expression across different cell types. | 2 |
| | Software for analyzing cell shape changes and dynamic distributions of fluorescent reporters at the cell membrane. | 7 |
| | A tool for accurately annotating cell types in single-cell RNA sequencing data using deep learning | 100 |
| | Develops an automatic prediction model for breast cancer proliferation scores from whole-slide histopathology images using deep learning techniques. | 207 |