All Competitors

Protein-protein docking scorer that ranks interface poses from image-encoded patches, swapping PIsToN's Vision Transformer for Vision Mamba.

EEG foundation model for brain-computer interfaces, pairing masked pretraining with a mixture-of-experts transformer across electrode montages.

Flow-matching model that predicts protein conformational ensembles across the order-disorder continuum, from folded domains to disordered chains.

All-atom generative model for de novo protein design using SE(3) flow matching over oriented residue rigid bodies.

Suite of large language models fine-tuned with LoRA to generate antigen-targeted antibody Fv sequences from an antigen and its epitope.

Molecular docking model that predicts protein-ligand binding poses with multi-stage Riemannian flow matching, yielding physically valid geometry.

fMRI foundation model trained on cortical flat-map videos with masked autoencoding, showing power-law scaling on brain activity reconstruction.

Proprietary family of multimodal protein language models (up to 102B parameters) for sequence and structure generation, editing, and design.

Efficient sequence-to-function transformer for regulatory genomics, matching Borzoi-class models while training in about a day on a single GPU.

Self-supervised single-cell foundation model that predicts masked gene embeddings in latent space using a joint-embedding predictive architecture.

Molecular graph transformer for ADMET property prediction, pretrained on 11M molecules under a joint SMILES-reconstruction and contrastive objective.

Protein conformational sampling framework that steers a retrained OpenFold with diverse secondary-structure predictions to recover alternative states.

Single-cell foundation model learning technology-agnostic cell embeddings by contrasting cell views rather than reconstructing gene expression counts.

Retrieval-augmented inverse folding model that fuses structural motif retrieval with a hybrid attention decoder to design sequences for a backbone.

Retrieval-augmented latent diffusion model for protein binder design, retrieving interfaces in a shared latent space across peptides and antibodies.

Protein structure autoencoder compressing backbone coordinates into a latent space, paired with a latent diffusion model for generative design.

Medical vision-language model that takes visual prompts on an image and returns answers grounded in pixel-level segmentation masks.

Autoregressive protein language model for antibody Fc domains, reinforcement-tuned to design variants with programmable Fc-receptor binding profiles.

Diffusion model over coarse-grained protein topology that samples diverse folds, handing them to RFdiffusion to build de novo protein backbones.

De novo ligand design framework that generates protein binders and small molecules by inverting gradients through a differentiable docking model.

Sequence-only interaction model scoring protein-protein and protein-ligand pairs plus functional annotation across whole proteomes in seconds.

Protein foundation model with 3B parameters, pretrained jointly on sequence and 3D structure via masked language modeling and diffusion denoising.

Graph diffusion transformer for in-context molecular design, adapting to new tasks from a few molecule-property demonstrations without fine-tuning.