All Competitors

Protein language model that fuses Gene Ontology knowledge graphs with masked language modeling, improving protein function and interaction prediction.

Protein language model pretrained on UniRef90 with masked language modeling and Gene Ontology annotation prediction, at 16 million parameters.

Antibody-specific language model trained on the OAS database for restoring missing residues and generating high-quality sequence representations.

Mass spectrometry proteomics foundation model that jointly embeds MS/MS spectra and peptides in one space, for open and error-tolerant search.

Rigid protein-protein docking model that predicts a complex from two unbound structures in one pass, with no candidate sampling or refinement.

Protein complex structure prediction model extending AlphaFold 2 with paired MSA processing and ipTM scoring for multi-chain, multimeric assemblies.

Protein model quality assessment predicting per-residue lDDT from a single structure, using ultrafast shape recognition to encode residue topology.

Residue-level binding site prediction from a bare protein sequence, ensembling six neural nets over protein, DNA/RNA and small-molecule interfaces.

Suite of six protein language models, including ProtBERT and ProtT5, trained on up to 393 billion amino acids without multiple sequence alignments.

Per-residue AlphaFold2 pLDDT confidence regressed from sequence by a bidirectional LSTM, with no structure prediction and no database lookup.

Protein structure and complex prediction from sequence, in a three-track network that reasons over alignments, distances, and 3D coordinates at once.

Protein structure prediction model that folds amino acid sequences into 3D structures with atomic accuracy, scoring a median GDT of 92.4 at CASP14.

Protein language model for zero-shot variant effect prediction, scoring mutations by log-odds from evolutionary sequences with no MSA or assay data.

Transformer protein language model trained on 250 million protein sequences that learns structural and functional representations without supervision.

Protein model accuracy estimation predicting per-residue lDDT plus signed residue-pair distance errors that become Rosetta refinement restraints.

Protein language model over byte-pair-encoded amino acid tokens, fine-tuned for protein family classification and binary interaction prediction.

Peptide retention time prediction for LC-MS/MS proteomics, from a genetic-algorithm search over convolutional and bidirectional GRU architectures.

Protein language model using a multiplicative LSTM over 24 million UniRef50 sequences to produce fixed-length embeddings for protein engineering.

Antibody paratope prediction model that identifies antigen-contacting residues from heavy and light CDR sequences alone, using CNN and RNN layers.