All Competitors

A holistic evaluation framework for protein foundation models, assessing 25+ models across 8 tasks using four-dimensional metrics: quality, novelty, diversity, and robustness.

Comprehensive NeurIPS 2023 benchmark for protein inverse folding, evaluating 8 models across single-chain, multi-chain, and de novo design tasks.

Python framework for building standardized protein structure datasets and benchmarks, with pre-processed data from PDB and AlphaFoldDB for deep learning evaluation.

A rigorous benchmarking study of scBERT and scGPT for cell type annotation, comparing foundation models against logistic regression baselines.

Benchmark suite of five biologically relevant tasks for evaluating protein sequence representation learning, covering structure, homology, and engineering.