Accurate and efficient spot detection for microscopy data
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A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
- protein
- protein-sequences
- protein-design
- representation-learning
GeneCompass
Learning cell communication from spatial graphs of cells
- tensorflow
- gnn
- glm
- cvae
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
Structural variant detection and association testing
Toolbox for the analysis of smFISH images.
- pattern-classification
- rna-localization
- segmentation
- smfish
NeuroAnatomy Toolbox: An R package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
- r
- neuroanatomy-toolbox
- cran
- neuron
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
- deep-generative-model
- deep-learning
- single-cell-data-integration
- single-cell-multiomics
The framework for quantification of neuronal anatomy
- neuroscience
- neuroanatomy-toolbox
- imagej
- imagej2
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
- analysis
- claude
- claudecode
- dna
Tool for precise, interactive, fast and scalable FISH spot detection
The repository host gives no description.
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
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
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.
Interpretable modeling of cellular responses to drug perturbations using cycle consistence learning
GNN-based gene-selection deep learning model for drug response prediction