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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1513–1536 of 2336 models
Drug-target interaction model that compresses any compound into a 15-bit hierarchical code, so billion-compound libraries can be screened in seconds.
Genetic language model predicting disease risk and cell-type-specific expression changes from up to 88 megabases of an individual's genome sequence.
Breast ultrasound generative foundation model that synthesizes conditioned images to train screening, diagnosis, and prognosis models.
Open-source PyTorch reproduction of AlphaFold 3 under Apache 2.0, matching or exceeding AF3 on protein-ligand, protein-protein, and RNA benchmarks.
Multimodal vision-text foundation model for brain CT and MRI, pretrained on roughly 10 million image-report pairs to act as a clinical copilot.
Regulatory genomics model predicting cell-type-specific RNA-seq coverage from DNA sequence, unifying transcription, splicing, and polyadenylation.
Anti-phage defense gene classifier pairing protein language model embeddings with genomic features to find immune systems outside defense islands.
Antimicrobial peptide generator fine-tuned from ProGen2, trained against a frozen ESM-2 encoder's latent space as an approximate function checker.
Genomic language model reading bacterial gene neighborhoods as sentences of protein-family tokens to predict anti-phage defense function.
Malate dehydrogenase sequence generator fine-tuned from ProGen2, with a latent-space distance term that lifted functional generations to 96.8%.
Protein language model fine-tuned to score any bacterial protein for anti-phage defense function, detecting homology too remote for HMM profiles.
Vision-language foundation model for precision oncology, pretrained on 50M pathology images and 1B text tokens via unified masked modeling.
Conditional diffusion model with cross-attention that synthesizes subject-specific 3D intrinsic connectivity networks from resting-state fMRI.
Protein expression prediction that pinpoints expression-governing residues by matching a language model landscape against measured fitness data.
Single-cell foundation model pretrained by federated learning, modeling expression as a cell-by-gene table rather than an ordered gene sentence.
Multimodal 80B-parameter protein-language model that answers natural language questions about protein function from sequence and structure.
CRISPR-Cas PAM specificity prediction directly from Cas protein sequence, plus computational evolution of Cas9 variants toward a chosen PAM.
Tumor microenvironment segmentation on H&E slides, labeling 13 tissue and cell components from a single model in semantic or panoptic form.
TCR-epitope binding prediction with a dual-branch transformer-CNN, inside a pipeline that ranks cancer neoepitopes from patient sequencing data.
RNA modification classification from nanopore direct-RNA current, resolving m6A, inosine, pseudouridine, Gm, and m1A at single-base resolution.
Gene function prediction over the Gene Ontology graph, inferring new GO annotations for a gene or gene product from the ones it already carries.
Metagenomic foundation model pretrained on 1.5 trillion base pairs of wastewater DNA and RNA for pathogen detection and biosurveillance.