davisidarta
Machine learning on high-dimensional data. Single-cell biology. Neuroimmunemetabolism. Postdoc at the Domingos' Lab.
University of OxfordUK
davisidarta's Stars
ossu/computer-science
🎓 Path to a free self-taught education in Computer Science!
marimo-team/marimo
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
scverse/scvi-tools
Deep probabilistic analysis of single-cell and spatial omics data
neurreps/awesome-neural-geometry
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
pymanopt/pymanopt
Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation
pachterlab/ffq
A tool to find sequencing data and metadata from public databases.
Dana-Farber-AIOS/pathml
Tools for computational pathology
Cerebras/gigaGPT
a small code base for training large models
theislab/ehrapy
Electronic Health Record Analysis with Python.
slowkow/harmonypy
🎼 Integrate multiple high-dimensional datasets with fuzzy k-means and locally linear adjustments.
saezlab/liana-py
LIANA+: an all-in-one framework for cell-cell communication
aidos-lab/pytorch-topological
A topological machine learning framework based on PyTorch
digitalcytometry/cytospace
CytoSPACE: Optimal mapping of scRNA-seq data to spatial transcriptomics data
Pseudomanifold/Aleph
A library for exploring persistent homology
davisidarta/topometry
Systematically learn and evaluate manifolds from high-dimensional data
GuipengLi/Dcluster
Clustering by fast search and find of density peaks
cwehmeyer/pydpc
Clustering by fast search and find of density peaks
aidos-lab/TARDIS
TARDIS: Topological Algorithms for Robust DIscovery of Singularities
BradBalderson/Cytocipher
Analysis methods for analysing single cell RNA-seq data; particularly with the goal of checking if tentative clusters of cells are significantly different to one another in terms of their gene expression.
dawe/schist
An interface for Nested Stochastic Block Model for single cell analysis
hj-n/zadu
A Python Library for Evaluating the Reliability of Dimensionality Reduction Embeddings
linnarsson-lab/FISHscale
Spatial analysis of FISH data
potulabe/symphonypy
Port of symphony algorithm of single-cell reference atlas mapping to Python
gd-vae/gd-vae
Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.
KenLauLab/dropkick
Automated cell filtering for single-cell RNA sequencing data
shchurch/countland
tools in python and R for analyzing biological count data, especially from single cell RNAseq
dissatisfaction-ai/scHierarchy
A toolking for cell type hierarchies: marker selection & consistent classification
Andrew-Draganov/GiDR-DUN
A simple implementation of UMAP, TSNE and GDR across frameworks and libraries
xiaoqunwang-lab/Allendigger
AllenDigger, a tool for spatial expression data visualization, spatial heterogeneity delineation and single cell registration based on Allen brain atlas
layer6ai-labs/UoMH