Genome modeling and design across all domains of life
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A collection of scientific methods, processes, algorithms, and systems to build stories & models.
- python
- machine-learning
- deep-learning
- pytorch
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.
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
- medical-imaging
- medical-ai
- deep-learning
- machine-learning
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
- drug-repurposing
- deep-learning
- drug-target-interactions
- toolkit
Foundation Models for Genomics & Transcriptomics
The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.
- cwt
- matlab
- cpp
- optimization
MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)
A python Two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
- source-energy-balance
- canopy
- soil
- radiometric-temperatures
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
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
BulkFormer: A large-scale foundation model for human bulk transcriptomes
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
Research experiments exploring uncommon quant techniques.
- analysis
- jupyter-notebook
- python
- quant
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
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
The repository host gives no description.
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
:game_die: Neutrino research
- physics
- neutrino
- neutrino-oscillations
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.