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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 817–840 of 1102 filtered models
Pocket-conditioned 3D ligand generator trained on its own predicted conformations, closing the train-inference gap that degrades diffusion sampling.
Two-stage backbone generator that designs protein domains separately, then weaves them into one long chain with an SE(3) diffusion assembly module.
Compact protein sequence generator adapted from Phi-3-mini with LoRA, emitting enzymes for ten named property classes from a plain-English prompt.
Controllable protein sequence generator adapted from Llama-3-8B with LoRA, prompted in plain English to emit enzymes from ten property classes.
Aligns structure, binding-pocket, text and molecular-dynamics encoders to a protein sequence anchor, giving frozen embeddings that transfer widely.
Intrinsic disorder prediction from protein sequence at proteome scale, distilling consensus disorder scores and AlphaFold2 pLDDT into one network.
Protein-protein interaction prediction from a language model that encodes both sequences jointly, trained on human PPIs and applied across species.
De novo protein backbone design with geometric-algebra attention, sampling designable structures whose secondary structure matches natural proteins.
Cryo-EM foundation model pre-trained on 65 million particle images, enabling zero-shot classification, pose clustering, and quality assessment.
Homology-aware protein language model on a recurrent xLSTM backbone, generating and scoring sequences from long contexts of unaligned homologs.
Protein inverse folding as a generative Markov bridge, refining a structure-derived sequence prior with a frozen protein language model.
Post-translational modification prediction from sequence and 3D structure, quantizing each residue's micro-environment into a per-PTM discrete token.
Biochemistry-aware inverse folding model that augments backbone geometry with physicochemical point clouds, reaching ~90% sequence recovery on CATH.
Estimation of model accuracy for protein complexes, predicting per-residue lDDT from Voronoi contact areas and contact-surface orientation features.
Protein subcellular localization from sequence, returning both a text label and a synthetic fluorescence image of the protein inside a given nucleus.
Peptide-MHC class I immunogenicity prediction fusing sequence, predicted structure, and biochemical properties for vaccine and neoantigen design.
Protein interface prediction from sequence alone, swapping hand-crafted features for frozen ProtT5-XL embeddings that hold up on remote homologs.
Phase separation prediction from sequence alone, pairing a protein language model with MD-trained conformational features to score every residue.
Inter-residue distance prediction that returns multi-peak distributions, so flexible regions yield several plausible distances instead of one.
Protein-ligand binding affinity prediction that fine-tunes ESM-2 and ChemBERTa-2 into a shared space where cosine similarity is the predicted pKd.
Cellular senescence prediction from protein sequence, pairing ESM-2 embeddings with a hybrid BiLSTM-CNN classifier at 86.43% test accuracy.
Protein language model that captures short- and long-range residue co-evolution through a dual pre-training objective, at 3B parameters.
Protein language model that explains single-site mutation effects in natural language and proposes new mutants from free-text instructions.
Long-context protein language model on a bidirectional Mamba backbone, outperforming ESM-2 by up to 30% at matched training token budgets.