All Competitors

Protein-protein interaction prediction with partner-specific interface localization from sequence. Screens one million pairs in under two hours.

Transformer that predicts protein-protein interactions at residue resolution, spanning mutations, PTMs, peptide-MHC binding, and disease variants.

Graph attention model that learns context-aware protein embeddings from protein-protein interaction, co-expression, and tissue association networks.

Paired-sequence protein language model that jointly encodes two interacting chains to predict interactions, binding affinity, and interface contacts.

Contrastive model built on a genomic language model that predicts physical protein-protein interactions across a microbial proteome in linear time.

Sequence-only interaction model scoring protein-protein and protein-ligand pairs plus functional annotation across whole proteomes in seconds.

Protein language model conditioned on ensembles of computed conformations, giving state-aware embeddings for interaction, localization, and function.

Protein-protein binding affinity prediction from sequence alone, pairing frozen protein language model embeddings with gradient-boosted trees.

Protein-protein interaction predictor fusing evolutionary and structural embeddings to screen bacterial and host-pathogen proteomes in minutes.

Sequence-only protein-protein interaction prediction at proteome scale. Each protein is embedded once, so a pair score compares two stored vectors.

MSA-based protein language model for unsupervised contact prediction, outperforming ESM2-15B with 111M parameters and leading on interface contacts.

Host-pathogen protein interaction predictor scoring bacterial effector and human protein pairs from frozen ESM-2 embeddings with a transformer.

Proteome-scale protein language model whose representations enable zero-shot protein-protein interaction and gene essentiality prediction.

Sequence-based protein-protein interaction predictor over ProtT5 embeddings that reaches 0.70 AUROC on the leakage-free gold standard benchmark.

Protein-protein interface prediction from 3D structure using face-centered surface fingerprints and geometric graph attention, at ROC AUC 0.89.

Plant immune receptor-ligand classifier that scores MAMP epitope immunogenicity from sequence, reaching 73% accuracy on a held-out test set.

Protein-protein interaction predictor that adds contact-guided dual attention and a geometric encoder to frozen protein language model embeddings.

Long-context protein language model that reads whole viral genomes, using interaction-guided sparse attention over contexts of 61,000 amino acids.

Protein representation model adding global fold-similarity and local substructure signals to masked pretraining, reaching 79.2 long-range contact P@L.

Single-cell foundation model inferring context-specific protein-protein interactions from cancer transcriptomes via a variational graph autoencoder.

Protein binding affinity prediction from sequence alone, returning pKd and per-residue interface labels instead of a yes-or-no interaction call.

Protein-protein interface embedding model built on Delaunay graphs, reused frozen for antibody-antigen affinity and antibody viscosity prediction.

E3 ubiquitin ligase-substrate interaction prediction from a LoRA-adapted protein language model fused with structure and subcellular localization.