TorchProtein is a machine learning library for protein science, built on top of TorchDrug. It provides representation learning models for both protein sequences and structures, as well as fundamental protein tasks like function prediction, structure prediction. Taking the advantage of TorchDrug, it is also easy to reuse abundant models from small molecules for proteins, or solve protein-molecule tasks such as binding affinity prediction.
Available as a part of TorchDrug.
TorchProtein is an open source library for protein representation learning. It encapsulates common protein machine learning demands in human-friendly data structures, models and tasks, to ease the process of building applications on proteins.
Start with basic data structures for manipulating proteins in this beginner tutorial.
Train a sequence-based encoder to predict properties of proteins, like fluoresence and stability.
Utilize the 3D structures of proteins via building structure-based encoders for property prediction.