Interpretable bilinear attention network with domain adaptation improves drug-target prediction.
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Data visualisation web components for the life sciences.
- biohackeu21
- bioinformatics
- visualization
- webcomponents
Accurate and efficient spot detection for microscopy data
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
A tool for cell instance aware segmentation in densely packed 3D volumetric images
- segmentation
- deep-learning
- bioinformatics
- neural-network
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
Toolbox for the analysis of smFISH images.
- pattern-classification
- rna-localization
- segmentation
- smfish
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
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
- epigenomics
- pattern-search
- data-visualization
- interactive-machine-learning
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics
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
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
3D shape analysis using deep learning
- cancer-biology
- cell-biology
- deep-learning
- geometric-deep-learning
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
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
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.
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