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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1801–1824 of 2336 models
Retrieval-augmented diffusion model that designs antibody CDR sequences by conditioning on structurally homologous CDR-like motifs from the PDB.
Diffusion model translating in both directions between protein sequences and fluorescence microscopy images to predict subcellular localization.
Walk-jump sampler that runs molecular dynamics in a smoothed, noised space of all-atom coordinates to generate peptide conformational ensembles.
3D CT vision-language model that drafts radiology reports, answers questions about volumes, and screens for disease from a masked-autoencoder encoder.
Computed tomography embedding model that compresses a whole DICOM CT volume into a 1,408-number vector for data-efficient downstream classifiers.
Contrastive transcriptome-text model for free-text search, zero-shot cell annotation and natural-language chat over bulk and single-cell RNA-seq.
Spatial transcriptomics prediction from H&E slides, inferring spot-level expression and tumor microenvironment composition in breast cancer.
Multimodal discrete-diffusion protein language model that co-generates amino acid sequence and 3D backbone structure from a single transformer.
Protein domain annotation model pairing an ESM-2 backbone with a probabilistic decoder, bringing language-model sensitivity to Pfam-style assignment.
Context-only BERT for bacterial protein function prediction, reading genomes as sentences of protein-cluster tokens with no sequence input.
Direct RNA nanopore basecaller pairing a densely connected 1D CNN and CTC decoder with a Random Forest classifier that demultiplexes 24 barcodes.
Wearable sensor foundation model pretrained on heart rate, accelerometer, skin temperature and other channels for activity recognition and imputation.
Vision-language chat model for 3D chest CT volumes, answering free-form questions and drafting radiology report findings from a frozen 3D encoder.
Codon-tokenized mRNA language model whose hierarchical loss scores codon errors by synonymity, pretrained on 15.3M curated antibody mRNAs.
Blind protein-ligand docking as a single transformer pass over distance matrices, at hundredths of a second per complex on one GPU.
RNA folding kinetics model that predicts the full distribution of first passage times from a few simulated examples in a single forward pass.
Fine-tuned Prosit predictor of spectra and retention time for citrullinated peptides, separating them from isobaric deamidation in MS searches.
Protein-ligand docking framework that picks the binding pocket by contrastive alignment, then refines the pose with bi-level iterative refinement.
Self-supervised contrastive model embedding cell and organelle dynamics from time-lapse microscopy for cell-state analysis without manual labels.
Mixed-modal DNA, RNA, and protein foundation model at 110M and 270M parameters, with in-context learning across sequence modalities.
Vision-language assistant that reads a whole gigapixel pathology slide, answering diagnostic questions and writing slide-level descriptions.
Echocardiography vision foundation model self-distilled on 20 million ultrasound images from 11 clinical centres, with swappable task decoders.
Joint embedding space for common SNPs and free-text clinical concepts, aligned by contrastive learning over GWAS, biobank and knowledge-graph pairs.