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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–10 of 10 filtered models
Generative model for chemically modified and macrocyclic peptides that builds molecules in HELM notation, supporting de novo design and infilling.
Conditional variational autoencoder for antimicrobial peptide design that disentangles sequence, function, and length for independent control.
De novo antibiotic design framework coupling a 6.4B-parameter protein language model with reinforcement learning to generate antimicrobial peptides.
Antimicrobial discovery model predicting compound potency against unseen bacterial strains and generating de novo antibiotics from pathogen genomes.
Protein sequence design by flow matching in a compressed language-model latent space, spanning peptides, antibodies, and antimicrobial peptides.
Antimicrobial peptide platform whose GPT-style generator is conditioned on E. coli or S. aureus activity, then filtered for potency and hemolysis.
Antimicrobial peptide discovery from metagenome-assembled genomes, labelling AMP residues with a LoRA-adapted ESM-2 token classifier.
Antimicrobial peptide generator fine-tuned from ProGen2, trained against a frozen ESM-2 encoder's latent space as an approximate function checker.
Antimicrobial peptide optimization framework pairing a transformer VAE latent space with constrained Bayesian optimization against an MIC oracle.
Antimicrobial peptide generator running denoising diffusion in the continuous ESM-2 embedding space, validated in mouse infection models.