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    83
  • Rank 390,557 (Top 8 %)
  • Language
    Jupyter Notebook
  • License
    GNU General Publi...
  • Created about 5 years ago
  • Updated over 3 years ago

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Repository Details

More Repositories

1

PHATE

PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
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2

MAGIC

MAGIC (Markov Affinity-based Graph Imputation of Cells), is a method for imputing missing values restoring structure of large biological datasets.
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3

SAUCIE

Python
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4

TrajectoryNet

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
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94
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5

scprep

A collection of scripts and tools for loading, processing, and handling single cell data.
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6

phateR

PHATE dimensionality reduction method implemented in R
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7

ReLSO-Guided-Generative-Protein-Design-using-Regularized-Transformers

a Transformer-based neural network for generating highly optimized protein sequences called Regularized Latent Space Optimization (RELSO)
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8

Multiscale_PHATE

Creating multi-resolution embeddings and clusters from high dimensional data
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47
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9

travelgan

Python
46
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10

graphtools

Tools for building and manipulating graphs in Python
Python
41
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11

DiffusionEMD

Code corresponding to the paper Diffusion Earth Mover's Distance and Distribution Embeddings
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27
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12

AAnet

Archetypal Analysis network (AAnet)
Jupyter Notebook
23
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13

TPHATE

Python
21
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14

MAGAN

Python
17
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15

MIOFlow

Jupyter Notebook
17
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16

phemd

Identifying cell subpopulational differences among single-cell biospecimens
R
12
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17

PECAN

PECAN: Persistent Condensation
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9
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18

SUGAR

Synthesis using Geometrically Aligned Random-walks
MATLAB
7
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19

CATCH

Learning cellular hierarchy from scRNAseq data
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7
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20

GSAE

Code from 'Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings"
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21

HeatGeo

Embedding with the Heat-geodesic dissimilarity
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6
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22

visualization_selection

Selecting the right tool for the job: understanding drawbacks and biases in visualization methods
Jupyter Notebook
6
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23

LearnableScattering

Learnable Geometric Scattering Network
Python
6
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24

CUTS

[MICCAI 2024] CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation
Python
5
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25

logicml

C
5
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26

CurveNet

Diffusion curvature and Hessian prediction using point samples from quadratic hypersurfaces
MATLAB
5
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27

Cell-Dynamics-Pipeline

Python
5
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28

scgraph

Graph-based methods for the analysis of single-cell data
Python
5
star
29

ImageFlowNet

Python
5
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30

GeoSinkhorn

Code for the paper Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds.
Python
4
star
31

LAD

Lipschitz Anomaly Discriminator
Python
4
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32

GSPA-manuscript-analyses

Learning meaningful representations of genes
Jupyter Notebook
4
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33

Gene-Signal-Pattern-Analysis

Learning meaningful representations of genes
Jupyter Notebook
3
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34

graph_fit

New ways of fitting a graph to vector data.
Jupyter Notebook
3
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35

pointcloud_scattering

Python
3
star
36

NN-LossLandscape-PHATE

Exploring the Geometry and Topology of Neural Network Loss Landscapes
Python
2
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37

scnn

Deep learning methods for the analysis of single-cell data
Python
2
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38

Trellis

2
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39

CSHL_ComputationalGenomics2022

2
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40

scMMGAN

Python
2
star
41

RiTINI

Regulatory Temporal Interaction Network Inference
2
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42

spARC

Denoising spatial transcriptomics data
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2
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43

GEFMAP

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2
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44

CSHL_ComputationalGenomics2023

2
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45

krishnaswamy-lab-site

Svelte
1
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46

phate-docker

Interactive command line docker script for running PHATE
Python
1
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47

NSCLC_pembro_sbrt

Jupyter Notebook
1
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48

GRASSY-Net

Python
1
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49

NeuronTransform

Python
1
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50

FMGAN

Python
1
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51

Condensation

Diffusion Condensation is a topologically-inspired machine learning algorithm that is used to identify populations of cells across granularities.
Jupyter Notebook
1
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52

Directed-Hierarchical-Gene-Networks

Python
1
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