Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1897–1920 of 2565 models
Phase separation prediction from sequence alone, pairing a protein language model with MD-trained conformational features to score every residue.
Chromatin accessibility prediction across 29 human immune cell types, using in-silico saturated mutagenesis to score constrained regulatory regions.
Inter-residue distance prediction that returns multi-peak distributions, so flexible regions yield several plausible distances instead of one.
Protein-ligand binding affinity prediction that fine-tunes ESM-2 and ChemBERTa-2 into a shared space where cosine similarity is the predicted pKd.
Cellular senescence prediction from protein sequence, pairing ESM-2 embeddings with a hybrid BiLSTM-CNN classifier at 86.43% test accuracy.
SMILES transformer pretrained to predict 113 RDKit molecular descriptors, giving embeddings that carry physicochemical properties into ADMET models.
Protein language model that captures short- and long-range residue co-evolution through a dual pre-training objective, at 3B parameters.
Frugal conditional diffusion model that samples human SNP haplotypes in PCA space, producing artificial genomes for a chosen continental ancestry.
Demultiplexer for direct RNA nanopore sequencing that basecalls the DNA barcode inside the RT adapter, reaching 99% precision on up to 96 barcodes.
Protein language model that explains single-site mutation effects in natural language and proposes new mutants from free-text instructions.
Long-context protein language model on a bidirectional Mamba backbone, outperforming ESM-2 by up to 30% at matched training token budgets.
Masked-autoencoder foundation model that pre-trains a 3D Residual Encoder U-Net on roughly 39,000 brain MRIs for volumetric image segmentation.
Dual-language transformer pretrained on paired protein and mRNA coding sequences, scoring protein and mRNA properties and generating optimized CDS.
Contrastive dual-encoder aligning T-cell receptor CDR3 and peptide epitope sequences in one latent space to rank which receptors bind which antigens.
Lasso peptide language model that adapts ESM-2 to threaded RiPP core sequences, supplying embeddings for cyclase substrate and activity prediction.
DNA methylation foundation model reconstructing genome-wide profiles from sparse input. Outperforms GrimAge2 aging clocks on mortality prediction.
Language model over whole-night sleep stage sequences that corrects automated sleep staging and supplies features for sleep disorder diagnosis.
Peptide representation model that DoRA-tunes ChemBERTa on 100,000 modified and bioactive peptide SMILES for therapeutic property prediction.
Pan-cancer digital pathology encoder: a ViT-L pretrained with DINOv2 on 400 million H&E patches drawn from 45,000 whole-slide images.
Reprograms a frozen single-target diffusion model for dual-target drug design by composing SE(3)-equivariant messages across two aligned pockets.
Single-cell perturbation prediction model that adds gene-level language embeddings from NCBI, UniProt, and Gene Ontology to scGPT representations.
Protein sequence design model that identifies each residue from the voxelized atomic microenvironment around it, reaching 68.33% accuracy on TS500.