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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 433–456 of 2565 models
Protein structure prediction and binder design in a single generative step, replacing AlphaFold3's iterative diffusion sampling with one forward pass.
Multimodal Q-former that fuses DNA sequence, gene context, protein function, and text for zero-shot variant interpretation with a frozen LLM.
Multiphoton pathology vision-language system turning one label-free breast section into virtual H&E, a margin heatmap, and a written report.
Sparse autoencoders trained on protein language model embeddings to expose interpretable features and drive zero-shot variant effect prediction.
370M-parameter ligand-conditioned discrete diffusion model that co-designs protein sequence and structure under explicit small-molecule constraints.
Sequence-based discrete-diffusion framework that designs peptide binders with specified agonist or antagonist behavior against GPCR targets.
Protein language model for variant effect prediction and de novo sequence design, conditioned on Gene Ontology embeddings of molecular function.
Protein sequence-structure co-design model conditioned on Gene Ontology function embeddings, sampling residues and backbone angles together.
Domain-specific foundation model for zero-shot plant root image segmentation, built on a MobileSAM backbone and trained across nine root datasets.
Protein conformational ensemble tokenizer that learns a discrete alphabet of states from molecular dynamics, reusable as a frozen feature layer.
Spatial transcriptomics deconvolution foundation model whose rank-based spot encoding transfers across tissues and platforms without retraining.
Multiscale graph neural network for fixed-backbone protein binder sequence design with a contrastive decoding algorithm to improve target selectivity.
Conditional discrete diffusion model for protein variant generation, with a calibrated identity dial controlling drift from a wild-type sequence.
Generative chemistry ensemble fine-tuned on 2.4M RNA-small molecule binding measurements, designing analogues around a seed compound.
Unified bio-language Mixture-of-Experts model spanning DNA, protein sequence and structure, and biological text across eight task families.
Transformer tractography model for mouse-brain diffusion MRI, guided by axonal priors learned from Allen Mouse Brain Connectivity Atlas streamlines.
Foundation model for paired ECG Lead-II and PPG waveforms, fusing the two through cross-modal attention and adaptive residual vector quantization.
Signed heterogeneous graph foundation model over the SIGMA-KG knowledge graph, predicting drug mode of action and drug-drug interactions zero-shot.
Latent diffusion model for PTM-aware protein sequence design, using ControlNet-style conditioning to steer generation toward chosen PTM sites.
Microbiome world model that treats a community as a set of taxa, scoring how well each member fits and predicting community dynamics zero-shot.
Multi-organ foundation model aligning histology images with spatial-transcriptomics profiles for zero-shot expression and survival prediction.
RNA inverse-folding language model that designs nucleotide sequences satisfying a target secondary structure, fixed bases, and coding constraints.
Discrete diffusion model for conditional antibody sequence design with germline-absorbing noising that focuses learning on somatic variation.
Virtual cell foundation model pretrained on over 23 million cells from 5,000 patient samples for drug target and biomarker discovery.