Code for the ProteinMPNN paper
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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.
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
- jupyter-notebook
- pandas
- federal-reserve
- gdp
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
- drug-repurposing
- deep-learning
- drug-target-interactions
- toolkit
Precision Medicine Knowledge Graph (PrimeKG)
- knowledge-graph
- precision-medicine
- therapeutics
- bioinformatics
The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.
- cwt
- matlab
- cpp
- optimization
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
- dna
- language-model
- variant-effect-prediction
- genomics
MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)
Wrapper for RDKit's RunReactants to improve stereochemistry handling
🏃 The go-to single-cell Foundation Model
- batch-correction
- cell-biology
- celltype-annotation
- denoising
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
Optimising chemical reactions using machine learning
- chemistry
- machine-learning
- optimization
- bayesian-optimization
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
Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
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
- epigenomics
- pattern-search
- data-visualization
- interactive-machine-learning
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
- foundation-models
- gpt
- single-cell
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.
- fine-tuning
- vgg16
- resnet18
- densenet121
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
- single-cell
- scrna-seq
- scatac-seq
- deep-neural-networks
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.
- benchmark
- bioinformatics
- cheminformatics
- computational-chemistry
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.