Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
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Official release of the ProGen models
- language-model
- protein
- generative-model
OmegaFold Release Code
Sequential regulatory activity predictions with deep convolutional neural networks.
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
- self-attention
- compound-protein-interaction
- transformercpi
- structure-free-virtual-sreening
Python package for image-based profiling
- cytominer
- microscopy
- morphological-profiling
- python
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
TypeDB Bio: Biomedical Knowledge Graph
- bioinformatics
- knowledge-graph
- knowledge-base
- drug-discovery
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection
DeepAEG: A model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
GNN-based gene-selection deep learning model for drug response prediction