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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 25–48 of 423 filtered models
DNA-binding residue prediction across folded domains and disordered protein regions, with contrastive training that suppresses cross-predictions.
RNA foundation model pretrained on 223 eCLIP experiments to predict base-resolution RBP binding, with frozen embeddings that transfer downstream.
Pan-cancer multi-omics foundation model that biases attention along central-dogma information flow, from DNA state through transcription to protein.
Genome-scale synthetic lethality prediction for any human gene pair from Gene Ontology annotations, no protein interaction network required.
Genomic foundation model on a Mamba, attention, and mixture-of-experts backbone, with 1M-token context for variant scoring and regulatory DNA design.
Cellular foundation models predicting how human cells respond to genetic and pharmacological perturbation, trained on petascale multi-omic data.
Biosynthetic gene cluster discovery in plant genomes, transferring supervision from microbial BGCs by label-free adaptation over Pfam-domain tokens.
Non-coding variant prioritization for rice GWAS loci, ranking SNPs by predicted effects on 12 chromatin features via a fine-tuned DNABERT-2.
Single-cell cancer model scoring driver-associated expression programs by projecting scRNA-seq through axes frozen from genotype-matched bulk tumors.
Multimodal microbiome foundation model pretrained on 1.8 million samples. Frozen representations transfer to biome classification and forecasting.
RNA and single-stranded DNA 3D structure prediction from sequence alone, with no MSA or language-model inputs and roughly 100x cheaper inference.
B-cell receptor DNA language model pretrained on antibody heavy-chain nucleotide sequences, with embeddings that outperform protein language models.
Mixed-modality metagenomic language model using bidirectional Mamba blocks to embed proteins within 20K tokens of coding and non-coding DNA.
Somatic mutation risk model predicting base-pair mutability from DNA sequence per COSMIC signature, separating passenger hotspots from cancer drivers.
Genomics foundation model that represents individual DNA fragments in a learned semantic space for cell-free DNA cancer detection and cell typing.
Transcription factor binding prediction pairing DNA sequence with base-resolution methylation and DNase accessibility for cell-type-specific calls.
Pan-fungal circRNA prediction from genome sequence and gene annotation alone, ranking candidate backsplice junctions without requiring RNA-seq.
Physics-informed graph neural network predicting metabolite concentrations from gene expression, generalizing zero-shot to unseen metabolites.
Enhancer RNA mapping model that locates eRNA loci genome-wide from DNA sequence and aggregated RNA-seq signal using a CNN-transformer architecture.
Cis-regulatory network reconstruction from DNA sequence, epigenomic tracks, and Hi-C priors, constrained by gene expression. 0.84 zero-shot auROC.
Plant genome foundation model for ab initio gene structure annotation, predicting genes, coding sequences, and exons at single-nucleotide resolution.
Ab initio gene annotation model that predicts gene boundaries and exon-intron structure from raw DNA, generalizing zero-shot to unseen species.
Multimodal foundation model for precision neurology that reconstructs a patient's molecular brain state from blood to predict disease progression.