TAPE (Tasks Assessing Protein Embeddings)
Benchmark suite of five biologically meaningful semi-supervised learning tasks for evaluating protein representations.
- from
- Computational Biology
- added
- 2026-10-10
- likes
- 0
similar
-
ProteinGym github.com
Large-scale benchmark of deep mutational scanning assays for evaluating protein fitness landscape models.
-
Protenix github.com
Trainable biomolecular structure-prediction framework for proteins, nucleic acids, ligands, and complexes with open training and inference pipelines.
-
TOSICA github.com
Transformer-based framework for one-stop interpretable cell-type annotation supporting cross-dataset and cross-species transfer.
-
DTINet github.com
Network-based framework integrating heterogeneous biological data for DTI prediction.
-
VirTues github.com
Spatial-proteomics foundation model learning marker-aware representations across proteins, cells, niches, and tissues from multiplexed imaging.
-
DeepDTA github.com
Deep learning model using CNNs on protein sequences and drug SMILES.
Computational Biology › Benchmarks & Datasets > Molecular, Protein & Drug Discovery: “Benchmark suite of five biologically meaningful semi-supervised learning tasks for evaluating protein representations.”