All Competitors

Unified drug design engine for protein-ligand structure prediction, binding affinity estimation, and compound generation from Isomorphic Labs.

Vision foundation model for the tree of life, scaling BioCLIP 2 to a ViT-H/14 backbone and more organism images for zero-shot species classification.

Cross-species multimodal foundation model of immunology and inflammation, harmonizing transcriptomics and histology into patient-level embeddings.

Structure-aware generative DNA language model pretrained on influenza genomes that forecasts future antigenic variants across regions and subtypes.

Protein-ligand scoring function that conditions probabilistic geometric potentials on language model priors to rank docked poses and binding affinity.

Vision-language foundation model linking human brain activation maps and neuroscience text for text-to-brain and brain-to-text generation.

Masked DNA language model for regulatory genomics with a motif-discovery regularizer for zero-shot TF motif recovery and variant effect prediction.

E(3)-equivariant diffusion model for macrocycle design that turns acyclic molecules into macrocycles, with a transformer choosing where to cyclize.

Protein structure tokenizer that encodes a whole structure globally, with each successive token adding detail for adaptive-length representations.

Protein backbone generator running a diffusion transformer over SaProt structural tokens, with an IPA token cache to speed up de novo design.

Single-cell perturbation prediction model using conditional flow matching to map control cells to perturbed expression distributions.

Protein structural homology search from sequence alone, embedding proteins so that structural similarity becomes a fast nearest-neighbor lookup.

Protein language model that predicts per-residue local energetic frustration directly from sequence, covering whole proteomes and disordered regions.

Graph-attention model that predicts A-to-I RNA editing from sequence and secondary structure, treating RNA as a graph with base-pairing edges.

Connects a frozen protein language model to a general LLM via a cross-modal projector, adding protein reasoning without catastrophic forgetting.

Full-atom SE(3)-equivariant diffusion model that inpaints binding interfaces to design proteins that bind DNA, RNA, and small molecules.

Masked language model for T-cell receptor and peptide-MHC binding prediction, with compositional pretraining and non-autoregressive decoding.

mRNA language foundation model trained on ~115M protein-coding sequences across the tree of life, unifying mRNA perception and generation.

Multimodal model that designs small molecules from transcriptomic and cell-imaging perturbation phenotypes with a rectified flow transformer.

Single-cell foundation model built on masked discrete diffusion, jointly generating gene identities and expression values from 59 million cells.

Joint-embedding predictive foundation model for echocardiography, pretrained on 18M cardiac ultrasound videos for artifact-robust representations.

Genome language model that adds evolutionary-rate prediction to pretraining, improving representations for variant effect and regulatory genomics.

Latent flow-matching method that repurposes protein language model embeddings to generate high-fitness protein variants without predictor guidance.

Pan-cancer model predicting spatial gene expression from H&E histology using conditional flow matching with a mixture-of-experts velocity field.