All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 97–111 of 111 filtered models
Walk-Jump Sampling
5758—Discrete generative model for antibody protein sequences combining MCMC walks on a smoothed energy landscape with one-step denoising jumps.
Protein60OpennessOpenCRISPR-1
1.2K80—AI-designed CRISPR-Cas9 gene editor generated by protein language models trained on 1.2 million CRISPR operons and shown to edit the human genome.
Protein16OpennessRoseTTAFold All-Atom
815936—Deep network that predicts structures of full biological assemblies: proteins, nucleic acids, small molecules, metals, and covalent modifications.
Protein54OpennessxTrimoPGLM
2153—Unified 100-billion-parameter protein language model combining autoencoding and autoregressive objectives for protein understanding and generation.
Protein30OpennessChroma
824——Diffusion model for programmable protein design that jointly samples structures and sequences, conditioned on symmetry, shape, or text prompts.
Protein53OpennessProGen2
705——Protein language models from 151M to 6.4B parameters, trained on over a billion sequences for sequence generation and zero-shot fitness prediction.
Protein55OpennessEvoDiff
675226—Discrete diffusion model for protein sequence and MSA generation, enabling controllable de novo design directly in sequence space without structure.
Protein84OpennessABGNN
5526—Huazhong University of Science and Technology +1 otherAugust 6, 2023antibodygraph_neural_networkprotein_design+1Antibody CDR design framework pairing a pretrained antibody language model with a hierarchical graph neural network for one-shot CDR generation.
Protein72OpennessMaskedProteinEnT
123—Structure-conditioned graph transformer trained with masked language modeling to learn residue encodings for inverse folding and antibody design.
Protein52OpennessRFdiffusion
3K1.3K—De novo protein design diffusion model that generates backbone structures conditioned on binding targets, symmetry constraints, and functional motifs.
Protein60Opennessalphafold_finetune
176113—AlphaFold fine-tuned on peptide-MHC and protein-peptide binding data for specificity prediction across MHC class I/II, PDZ, and SH3 domains.
Protein75OpennessEquiFold
12952—Protein structure prediction model pairing SE(3)-equivariant networks with a coarse-grained representation to fold sequences fast, without MSA inputs.
Protein46OpennessProteinMPNN
1.8K1.9K—Message passing neural network for fixed-backbone protein sequence design. Achieves 52.4% native sequence recovery, far surpassing Rosetta's 32.9%.
Protein85OpennessProtGPT2
—8698.2KAutoregressive protein language model based on GPT-2 that generates de novo protein sequences sampling unexplored regions of protein space.
Protein54Openness