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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Structure-based molecular generation guided by imputed ligand electron density, assembling drug-like compounds into a pocket fragment by fragment.
Protein language model that generates paired heavy and light chain human antibodies from an antigen prompt, with binders validated in vitro.
Protein and RNA sequence annotation that also names the residues driving each label, learned from sequence-level supervision alone.
Retention time prediction for peptides whose post-translational modifications were never seen during training, using molecular-structure encodings.
Protein-ligand binding affinity prediction from multimodal representations. Retains accuracy on predicted rather than crystal complex structures.
Contact map and interface residue prediction for intrinsically disordered regions from sequence, outperforming AlphaFold-Multimer and AlphaFold3.
DNA- and RNA-binding residue prediction from a nucleic-acid-adapted protein language model and an equivariant graph network over protein structure.
Geometric foundation model matching enzymes to the reactions they catalyze, trained on 1.5 million structure-informed enzyme-reaction pairs.
Fragment-ion intensity prediction for cross-linked peptides, covering cleavable DSSO and DSBU chemistries alongside non-cleavable DSS and BS3.
Antibody CDR sequence and structure co-design from the whole antigen, using a relation-aware equivariant graph network with no specified epitope.
Cryo-EM heterogeneous reconstruction that models particles as one of K neural fields, resolving compositional and conformational states ab initio.
PROTAC degrader generation pipeline that screens target-binding fragments, then builds molecules under structure and physicochemical constraints.
Graph transformer over 3D protein structures predicting solvation free energy, hydrodynamic radius, diffusion constants, and molecular volume.
Multimodal foundation model integrating protein sequence, structure, and natural language to model and generate protein phenotypes across scales.
Antibody language model trained on human clonal families, proposing mutations that mimic in vivo affinity maturation for binding and stability.
HLA class II presentation and CD4 epitope prediction from peptide sequence, built on a protein language model with learned allele deconvolution.
Codon optimization framework pairing a frozen ProtBert encoder with a masked codon head, so every designed coding sequence translates back exactly.
Antibody sequence design conditioned on antigen structure, generating CDRs or full variable regions without epitope annotation or docked frameworks.
Generates free-text descriptions of protein function, catalytic activity, subcellular localization, and domains from sequence alone.
Protein structure tokenizer that discretizes backbones into 512 discrete tokens and reconstructs all-atom structures, including side chains.
Per-residue prediction of where a receptor domain can be inserted into a protein without breaking it, for building allosteric and inducible switches.
Antibody structure prediction returning backbone and side-chain coordinates in about a second, driven by a 650M-parameter antibody language model.