GPfates
Cell fate modeling software
Software to model transcriptional cell fates as mixtures of Gaussian Processes
19 stars
5 watching
4 forks
Language: Python
last commit: over 8 years ago
Linked from 1 awesome list
Related projects:
| Repository | Description | Stars |
|---|---|---|
| | Tools and methods to analyze gene expression data in relation to spatial coordinates | 151 |
| | A MATLAB package for modeling cell differentiation and lineage relationships from single-cell gene expression data. | 11 |
| | A software framework for integrating multi-omics data from single cells | 388 |
| | Software for modeling and prediction with multiple output Gaussian processes | 48 |
| | A toolbox for incorporating enzyme constraints into genome-scale models of biological systems | 66 |
| | Develops a method to learn shared latent structure between biomedical images and gene expression data | 25 |
| | An unsupervised learning and generative models library for Python, focusing on probabilistic models and efficient computation. | 119 |
| | A lightweight library for building Gaussian Process models in Python | 297 |
| | Algorithmic software for analyzing single-cell RNA sequencing data to reconstruct T cell receptor sequences. | 14 |
| | 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 |
| | A package for normalizing gene expression matrices using various techniques. | 9 |
| | An open-source Python package for applying Gaussian processes to images and hyperspectral data for reconstruction and Bayesian optimization. | 57 |
| | 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 |
| | This project provides a set of tools and techniques to design and improve diffusion-based generative models. | 1,447 |
| | A PyTorch-based framework for training and studying artificial species in bio-inspired environments | 72 |