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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1297–1320 of 2336 models
RNA language model that reads full-length transcripts up to 10,000 nucleotides, pairing bidirectional state space layers with multi-head attention.
Protein-protein binding interface prediction from conformational ensembles, resolving interfaces in flexible and intrinsically disordered regions.
Histopathology foundation model pretrained with BEiT masked image modeling on 11M+ tissue image tiles for cancer diagnosis and survival prediction.
Clinical imaging encoder multitask-pretrained across X-ray, mammography, dermoscopy, fundus, ultrasound, CT, and histopathology for few-shot transfer.
Slide-level pathology foundation model that vector-quantizes tile patch tokens at 64x compression, keeping spatial detail for whole-slide analysis.
Generative foundation model that co-generates sequence and 3D coordinates for proteins, small molecules, and crystals under functional objectives.
De novo small molecule generation that assembles drug-like graphs atom by atom, pretrained on cheap property proxies and finetuned per objective.
Multimodal LLM unifying 12-lead ECG time series, ECG images, and text for grounded, clinician-aligned electrocardiogram interpretation.
Neurotoxicity prediction for short peptides and full-length neurotoxins, with separate ESM-2 models matched to each sequence length regime.
Cross-domain molecular foundation model encoding small molecules, protein pockets, and their complexes in 2D and 3D on one Transformer backbone.
Full-atom flow matching model that generates a ligand and the induced-fit holo pocket together, starting from an apo binding site.
Protein structure embedding model that compresses each 3D fold into a single fixed-length vector for proteome-wide similarity search and clustering.
Dual-target protein sequence design conditioned on two receptor structures at once, combining a heterogeneous graph network with ESM-2 features.
Latent diffusion model generating 3D drug-like molecules and inorganic crystals from one shared all-atom autoencoder and Transformer denoiser.
Single-cell RNA-seq foundation models combining masked modeling with ontology supervision to classify cell states across unseen donors and diseases.
Protein-conditional RNA design model that generates binding RNA sequences for any target protein, with no post-generation optimization step.
PET/CT foundation model pretrained by cross-modal masked autoencoding on whole-body scans, for tumor lesion segmentation and lymphoma staging.
Promptable 3D segmentation for particle picking in cryo-electron tomography, conditioned on a reference subtomogram to detect any target complex.
Drug-combination safety prediction that fuses molecular structure, pathway knowledge, cell viability, and transcriptomic response to perturbation.
Genomic language model for variant effect prediction that scores deleterious mutations from a single DNA sequence, with no alignment at inference.
Chest X-ray encoder that detects CT-level abnormalities by aligning radiographs with 3D CT volumes and radiology reports in a shared embedding space.
Secondary metabolite structure prediction from microbial biosynthetic gene clusters, generating SMILES strings from Pfam functional-domain tokens.
Patch-based 3D diffusion model that generates teravoxel-scale virtual mouse brain volumes conditioned on spatially resolved gene expression.