A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
- drug-repurposing
- deep-learning
- drug-target-interactions
- toolkit
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A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Reference mapping for single-cell genomics
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)
🏃 The go-to single-cell Foundation Model
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.