Repository Index

Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk

• bioinformatics
• exact-optimization
• metabolomics
• paired-data

Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell

• histology
• wsi-images
• pan-cancer-analysis
• genomics

Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome

• cancer-genomics
• cnv-detection
• single-cell
• phylogeny

🏃 The go-to single-cell Foundation Model

• batch-correction
• cell-biology
• celltype-annotation
• denoising

The repository host gives no description.

Learning cell communication from spatial graphs of cells

• tensorflow
• gnn
• glm
• cvae

MCP server for spatial transcriptomics analysis through natural language interfaces.

• bioinformatics
• cell-communication
• deconvolution
• machine-learning

Predicting Cell Health with Morphological Profiles

• carpenter-lab
• morphological-profiling
• crispr
• cell-painting

CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer

• cancer
• foundation-model
• single-cell

3D shape analysis using deep learning

• cancer-biology
• cell-biology
• deep-learning
• geometric-deep-learning

Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics

• bioinformatics
• cell-type-deconvolution
• computational-biology
• deconvolution

Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.

• postgres
• postgresql
• python
• infectious-disease

DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.