TorchProtein & PEER Protein Sequence Benchmark Release

MilaGraph released TorchProtein, a new version of TorchDrug powered with a suite of tools for protein sequence understanding. Quoting the authors:

“ TorchProtein encapsulates many complicated yet repetitive subroutines into functional modules, including widely-used datasets, flexible data processing operations, advanced encoding models, and diverse protein tasks.

With TorchProtein, we can rapidly prototype machine learning solutions to various protein applications within 20 lines of codes, and conduct ablation studies by substituting different parts of the solution with off-the-shelf modules. Furthermore, we can easily adapt these modules to our own needs, and make systematic analyses by comparing the new results to a benchmark provided in the library.”

Simultaneously, the authors present PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding, a new benchmark of 17 protein understanding tasks grouped into 5 categories (Function Prediction, Localization Prediction, Structure Prediction, Protein-Protein Interaction Prediction, Protein-Ligand Interaction Prediction) already available in TorchProtein. ProtBert and ESM-1b have been probed on PEER (and ESM-2 is expected to arrive as well).