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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1873–1896 of 2565 models
Genomic language model on a recurrent xLSTM backbone, with reverse-complement equivariant blocks and single-nucleotide context up to 32,768 bases.
Homology-aware protein language model on a recurrent xLSTM backbone, generating and scoring sequences from long contexts of unaligned homologs.
RNA foundation models that learn their own character-level tokenization instead of fixed nucleotide or k-mer vocabularies. Sizes run 8M to 650M.
Molecular property prediction from 3D structure for assays with dozens of labels, pretrained by extreme denoising plus DFT and LLM auxiliary labels.
Imaging-genetics foundation model pairing SNP genotypes with brain-MRI phenotypes by contrastive learning to surface many-to-many associations.
Metagenomic read binning from tetranucleotide k-mer profiles, using a contrastive two-layer encoder trained on split halves of unlabeled reads.
Protein inverse folding as a generative Markov bridge, refining a structure-derived sequence prior with a frozen protein language model.
Cell microscopy foundation model with a 1.9-billion-parameter masked autoencoder producing embeddings that stay consistent across screening batches.
Post-translational modification prediction from sequence and 3D structure, quantizing each residue's micro-environment into a per-PTM discrete token.
RNA language model built from bidirectional Mamba2 blocks with a flash-attention head, pretrained on 100 million sequences up to 2,048 nucleotides.
Cell phenotyping model for spatial proteomics using a language-informed vision transformer to classify cell types zero-shot across marker panels.
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.
Diffusion autoencoder framework that morphs H&E tiles until a pathology classifier flips, exposing the morphology behind the prediction.
Whole-genome somatic copy-number aberration prediction from bulk RNA-seq alone, with one pan-cancer model covering 33 tumor types.
Hi-C contact map super-resolution that adds interaction frequencies imputed from DNase-seq accessibility so one cell line's model transfers to others.
Molecular scaffold optimization that grafts generated fragments onto a lead compound, guided by Bayesian search in a conditional VAE latent space.
Peptide-MHC class I immunogenicity prediction fusing sequence, predicted structure, and biochemical properties for vaccine and neoantigen design.
Protein subcellular localization from sequence, returning both a text label and a synthetic fluorescence image of the protein inside a given nucleus.
DNA methylation foundation model over 49,156 array CpG sites. Imputes missing values, embeds samples, and predicts epigenetic age and disease risk.
Single-cell RNA-seq foundation model pretrained only on malignant cells, for zero-shot batch integration and drug response prediction in tumors.
Protein interface prediction from sequence alone, swapping hand-crafted features for frozen ProtT5-XL embeddings that hold up on remote homologs.
Poly(A)-tail length change predicted from mRNA 3' UTR sequence in maturing oocytes, scoring how single-nucleotide variants disrupt tail lengthening.