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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 25–48 of 2335 models
Single-cell perturbation prediction model that splits a transcriptional response into systematic, perturbation-specific, and population-level parts.
Long-context RNA foundation model reading whole mRNA transcripts at single-nucleotide resolution, pretrained at a native 10,240 nt context.
Designs macrocyclic peptide molecular glues bridging two target proteins from sequence alone, validated as VHL-recruiting degraders in cells.
Protein-ligand co-folding model on the OpenFold3 architecture, trained on PDB structures through June 2025 with inference-time chemical steering.
Bioacoustic encoder for birdsong that resolves individual syllables at 5 ms, using asymmetric spectrogram patches and Voronoi masked pretraining.
Drug- and dose-conditioned latent transition predictor pretrained on the Tahoe-100M perturbation atlas and transferred frozen to tumor RNA-seq.
Cryo-EM pose estimation conditioned on a reference volume handed in at inference, assigning particle orientations zero-shot on unseen structures.
Genomic foundation model that pairs 650 kb of gene-centered DNA with transcription factor activity to predict expression in unseen cell types.
RNA co-design model generating sequence and 3D backbone together, with SE(3) flow matching over coupled base-centered and sugar-centered frames.
Self-supervised transformer fusing Enformer DNA embeddings with ATAC-seq accessibility into reusable 256-dimensional genomic window embeddings.
Gene regulatory network inference from scRNA-seq that returns directed TF-to-target edges in one forward pass, with no per-dataset refitting.
Accelerated MRI reconstruction that plugs a pretrained consistency-model prior into regularization by denoising, using four network evaluations.
Variant effect and disease phosphosite prediction that fuses frozen ESM-2 embeddings with normal-mode protein dynamics over AlphaFold residue graphs.
Binary protein classification over frozen ESM3 embeddings, using transformer contextualization and learned attention pooling instead of fixed pooling.
Long-context co-folding model for protein, nucleic-acid and ligand assemblies, folding systems up to 16,384 residues on a single GPU.
Self-supervised transformer pretrained on cell-free RNA expression profiles, built as a shared substrate for downstream disease-detection models.
Cross-modal continued pretraining on curated mass-spectrometry proteomes lifts a 70M single-cell model past RNA-only checkpoints far larger.
World model that simulates a human cell as one persistent state, propagating drug and gene perturbations from DNA through to whole-cell morphology.
Designs RNA and DNA aptamers against protein targets by backpropagating binding and anti-binding objectives through a frozen all-atom predictor.
Histopathology tile encoders reach 22M parameters by distilling billion-parameter teachers through their frozen class and patch tokens alone.
Pan-cancer clinico-genomic model for treatment response and survival prediction, transferring zero-shot to unseen hospitals and cancer types.