PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
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Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.
- postgres
- postgresql
- python
- infectious-disease
Official implementation of JAMIE, Joint variational Autoencoders for Multimodal Imputation and Embedding
- autoencoder
- imputation
- integration
- multimodal
A flexible Julia toolkit for high-dimensional cellular profiles
- julia
- morphological-analysis
- high-content-screening
scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection
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.
Analysis of cell migration in Igor Pro
- igor
- imagej
- cell-migration
- tracking
The repository host gives no description.
XitoSBML - the spatial SBML plugin for ImageJ
- sbml
- systems-biology
- spatial-sbml-plugin
- imagej
Interpretable modeling of cellular responses to drug perturbations using cycle consistence learning
Vendor-agnostic, FHIR-Genomics-aligned API contract for cross-vendor NGS interpretation. JSON Schema + TypeScript + Python pydantic.
gateway for segmentation data to Rstats & visualization with ggplot2 - in development
- visualization
- fluorescence-data
- ggplot
DeepAEG: A model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
Python library for statistical analysis of mRNA and protein distributions in fluorescent microscopy images
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.
GNN-based gene-selection deep learning model for drug response prediction