Single Cell Multi-omics deep clustering
-
Updated
Feb 8, 2024 - Python
#
multiomics-data
Here are 6 public repositories matching this topic...
MerCat2: python code for versatile k-mer counting and diversity estimation for database independent property analysis for metaome data
python
diversity
plotly
protein
dask
fastq
k-mer-counting
k-mer-frequency
divideandconquer
metagenomic-analysis
metatranscriptomic-analysis
kmer-frequency-count
nucleotides
diversity-estimation
database-independent-analysis
multiomics
multiomics-data
-
Updated
Jun 12, 2024 - HTML
MOVIS: A Multi-Omics Software Solution for Multi-modal Time-Series Clustering, Embedding, and Visualizing Tasks, by Aleksandar Anžel, Dominik Heider, and Georges Hattab
visualization
machine-learning
bioinformatics
time-series
cross-platform
clustering
web-app
exploratory-data-analysis
time-series-analysis
multiomics
multiomics-data
-
Updated
May 17, 2022 - Python
Code for paper Multiomics dynamic learning enables personalized diagnosis and prognosis for pan-cancer and cancer-subtypes
-
Updated
Oct 29, 2023 - Python
Network Regression Embeddings reveal cell-type Transcription Factor coordination for target gene (TG) regulation
transcription-factors
protein-interaction
network-regularization
gene-expression-profiles
transcriptional-regulatory-network
single-cell-analysis
ppi-networks
network-lasso
multiomics-data
gene-regulatory-network-inference
bioinformatics-software
transcription-factor-coordination
regularization-embeddings
regression-embeddings
predictor-interactions
network-guided-regression
regression-with-prior-knowledge
network-based-inference
netrem
-
Updated
May 18, 2024 - Jupyter Notebook
coxnnet v1 and v2 models updated to work with Python3.
-
Updated
May 1, 2021 - Jupyter Notebook
Improve this page
Add a description, image, and links to the multiomics-data topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the multiomics-data topic, visit your repo's landing page and select "manage topics."