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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 913–936 of 1102 filtered models
RNA language model adapted from ESM-2 by cross-modality transfer learning, matching RNA-native baselines with 1/8 the trainable parameters.
Peptide collision cross section predictor for ion-mobility proteomics, built on frozen protein language model features plus ion charge and mass.
Sequence-conditioned diffusion model that samples backbone conformational ensembles for intrinsically disordered proteins without MSAs or simulation.
A 3D UNETR++ transformer that enhances experimental cryo-EM density maps, improving map-model agreement and automated de novo structure modeling.
Antibody language model that generates full-length human B-cell receptor heavy and light chains by fine-tuning a general protein language model.
Structure-based Gene Ontology annotation that proposes candidate functional regions in a residue graph before reading them out as GO terms.
Open-source reproduction of AlphaFold 3 that predicts structures of proteins, DNA, RNA, and small-molecule ligands, including their mixed complexes.
Protein-peptide docking that builds all-atom complexes by diffusion, covering 92 residue types including post-translational modifications.
End-to-end framework predicting protein structure and mutational fitness from a single sequence, with five-fold faster inference than ESMFold.
Multimodal contrastive model aligning protein structure and sequence with ligand conformation and graph to retrieve binders without docking.
Peptide-spectrum match rescoring for proteomics, scoring a full MS/MS spectrum against a candidate peptide without training on decoy sequences.
Template-guided protein design model that miniaturizes, diversifies, or expands a natural protein by decoding a fixed-size probabilistic encoding.
All-atom protein generation model that samples side chains, backbone, and sequence together from a single diffusion process over atom coordinates.
Conditional diffusion model that generates P-type ATPase backbone conformations in a specified E1, E1P, E2P, or E2 functional state.
Chemical language model reading modified and cyclic peptides as SMILES, fine-tuned to predict passive membrane diffusion of macrocycles.
Enzyme redesign framework built on a structure-to-sequence protein network, scoring mutants and generating sequences without retraining.
Text-to-text biological language model spanning molecules, proteins, and text, adding IUPAC names and multi-task instruction tuning to BioT5.
Pretrains on EC, GO, InterPro and Gene3D ontology tokens with no amino acids, building a protein feature space from curated function alone.
De novo peptide binder design framework that targets specific motifs, including disordered regions and conserved epitopes, from target sequence alone.
Reshapes a frozen ESM-2 latent space by contrasting it against EC, GO, InterPro and Gene3D ontology tokens for function-aware protein embeddings.
Generates protein sequences from EC, GO, InterPro and Gene3D prompts by cross-attending an ESM-2 decoder onto an annotation transformer encoder.
Extends an ESM-2 token embedding matrix with EC, GO, InterPro and Gene3D tokens so one transformer reads residues and ontology terms together.
Genome language model that embeds a genome as a set of contextualized protein embeddings, pretrained on over 100,000 viruses for viromics.