All Competitors

Antibody-antigen binding prediction from heavy chain, light chain, and antigen sequence, scoring 0.946 AUROC on a SARS-CoV-2 benchmark.

Open-source framework for building RNA and DNA foundation models, featuring WCED pretraining for transcriptomics and SNP-aware encoding for genomics.

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

Open model that jointly predicts biomolecular structure and small-molecule binding affinity, approaching FEP+ accuracy in seconds on a single GPU.

Cross-modal co-embedding of biosynthetic gene clusters and natural products, enabling bidirectional retrieval between gene cluster and compound.

Multimodal clinical foundation model reasoning jointly over 2D and 3D medical images, ECG time-series, and text reports across nine clinical domains.

De novo small-molecule generation inside a protein pocket, diffusing ligand atoms and pocket side chains together so the site adapts as it binds.

Protein conformation ensemble generation aligned to force-field energies, calibrating an AlphaFold 3-style diffusion model against MD thermodynamics.

Vision foundation model for the tree of life, trained on 214 million organism images across 952,000 taxa for zero-shot species classification.

Plant DNA-binding protein prediction that averages a ProtT5 sequence-embedding classifier with a SaProt structure-aware one at the score level.

Antibody caninisation model generating canine framework regions around given CDRs, released with a dataset of 430,000 canine antibody sequences.

Protein-ligand docking model for high-throughput virtual screening, predicting binding poses with graph neural networks at low computational cost.

DNA-LLM reasoning model fusing genome foundation model embeddings with an LLM to produce step-by-step pathway and variant effect explanations.

Instruction-tuned LLM series for multi-property molecule optimization that improves named drug properties while preserving those already in range.

mRNA optimization model that raises codon adaptation, tRNA adaptation, and folding stability at once while preserving the encoded protein sequence.

Molecular embedding model that turns SMILES into SE(3)-invariant vectors for property prediction, similarity search, and compound clustering.

Diffusion protein language model for de novo design conditioned jointly on GO terms, InterPro domains, EC numbers, motifs, and backbone structure.

Missense variant effect predictor that scores mutations from Δ-embeddings — wild-type minus mutant protein language model representations.

Intrinsically disordered region function prediction, scoring every residue for five binding subtypes plus disordered flexible linkers.

RNA conformational ensemble generation with a diffusion model, sampling excited states and folding pathways from one structure without MSA input.

Linear B-cell epitope prediction for cancer antigens, pairing ESM-2 embeddings with an MLP classifier; ROC-AUC 0.94 on a held-out IEDB benchmark.

Cyclic peptide design conditioned on target protein structure, generating all four cyclization types via all-atom, all-bond harmonic SDE modeling.

De novo protein binder design that recasts structure-predictor confidence as an energy function, replacing ipTM as the hallucination objective.