Repository Index

Official repository for the Boltz biomolecular interaction models

• binding-prediction
• drug-discovery
• protein-structure

Chai-1, SOTA model for biomolecular structure prediction

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

• drug-repurposing
• deep-learning
• drug-target-interactions
• toolkit

Sequential regulatory activity predictions with deep convolutional neural networks.

GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations

Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star

• dna
• language-model
• variant-effect-prediction
• genomics

Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk

• bioinformatics
• exact-optimization
• metabolomics
• paired-data

RNA-seq prediction with deep convolutional neural networks.

MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)

A Network Integration Approach for Drug-Target Interaction Prediction

OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

• disentanglement
• drug-discovery
• genomics
• perturbation

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

Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

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

code to run sei and obtain sei and sequence class predictions

PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.

Predicting Cell Health with Morphological Profiles

• carpenter-lab
• morphological-profiling
• crispr
• cell-painting

PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"

Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.

• postgres
• postgresql
• python
• infectious-disease