All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–12 of 12 filtered models
LYNX
9——Spatial multi-omics integration model aligning RNA, protein, metabolomics, and histology to map cell-state gradients and cell-cell interactions.
Spatial omicsSingle-cell28Openness- Max Delbrück Center for Molecular MedicineJune 24, 2026gene_expressiongenerativerepresentation_learning+4
Supervised variational autoencoder that learns a tissue-aware latent space for bulk RNA-seq, trained on harmonized TCGA, GTEx, and ARCHS4 data.
RNA84Openness Cellpin
———Variational autoencoder trained on scRNA-seq and applied frozen to impute unmeasured genes and denoise spatial transcriptomics profiles.
Spatial omicsSingle-cell22OpennessChreode
———University of North Carolina at Chapel Hill +2 othersMay 27, 2026cell_fate_predictioncrispr_perturbationdevelopmental_trajectory_modeling+8Cell world model pretrained on a 2.4M-cell mouse embryonic atlas, predicting one-step transcriptional state transitions and perturbation response.
Single-cell26OpennessAnewOmni
842—All-atom generative foundation model that designs small molecules, peptides, and nanobodies against a target binding site from a single checkpoint.
ProteinSmall molecule63OpennessPLUM
1——Conditional variational autoencoder for antimicrobial peptide design that disentangles sequence, function, and length for independent control.
Protein56OpennessRADiAnce
———Retrieval-augmented latent diffusion model for protein binder design, retrieving interfaces in a shared latent space across peptides and antibodies.
Protein26OpennessMORPH
156—Single-cell perturbation-response model that predicts transcriptomic and imaging outcomes of unseen genetic perturbations via a VAE with attention.
Single-cellImaging7OpennessTahoe-100M-SCVI
1.7K123—scVI variational autoencoder trained on the Tahoe-100M drug-perturbation atlas, giving a 10-dimensional embedding of treated cancer cell states.
Single-cell93OpennessCryoLens
19——Variational autoencoder that learns interpretable representations of protein subtomograms from cryo-ET, trained on 5.8 million synthetic particles.
Imaging74OpennessscVI (CELLxGENE Census)
1.7K2.4K—Variational autoencoder pretrained on 74 million human single-cell transcriptomes from the CELLxGENE Census for batch correction and cell typing.
Single-cell96OpennessRfamGen
4260—Generative RNA design model that samples family sequences from a VAE latent space constrained by Rfam covariance models and consensus structure.
RNA10Openness