All Competitors

Multimodal foundation model integrating spatial transcriptomics, H&E histopathology, and pathway scores for single-cell niche discovery.

Predicts protein complex stoichiometry from amino acid sequence alone, ranking copy numbers in seconds and exporting AlphaFold3-ready JSON files.

Transformer that generates multi-species antibody and nanobody framework regions at the mRNA level, conditioned on input CDRs, across six species.

Generative virtual-cell model predicting whole-transcriptome responses to unseen compounds and genetic perturbations, from cell lines to organoids.

Molecular reasoning model built on DeepSeek-7B, using chain-of-thought and reinforcement learning for property prediction, generation, and reactions.

Coding-sequence foundation model for mRNA design, pretrained as a BART denoising encoder-decoder on mRNA from nine taxonomic groups.

Edit-based flow-matching model that proposes protein variants by learning insertions, deletions, and substitutions on a template sequence.

DNA language model that replaces fixed tokenization with conservation-guided patching, letting models up to 10x smaller match top genomic benchmarks.

Cell-centric microscopy foundation model that distills morphology and microenvironment views into a unified embedding for virtual spatial omics.

Paired-sequence protein language model that jointly encodes two interacting chains to predict interactions, binding affinity, and interface contacts.

Diffusion generative model for structure-based peptide inverse folding, pairing a geometric GNN encoder with a Transformer denoiser.

Hierarchical language model for atlas-level cell-type annotation of scATAC-seq data that annotates new query datasets without retraining.

Post-hoc method that restores monotonic scaling to ESM-2 embeddings, yielding Matryoshka-style nested representations for variant effect prediction.

Bacterial proteome foundation model that learns contextualized gene and whole-genome representations from tens of thousands of complete genomes.

EEG-to-text foundation model that turns raw recordings into clinically grounded natural-language narratives instead of fixed-label classifications.

Cross-modal protein encoder that aligns ESM-2 sequence embeddings with ProteinMPNN structure embeddings in a shared space for cross-modal retrieval.

Neural Hamiltonian flow for protein sequence generation with inference-time control over composition and net charge via analytical bias potentials.

Self-supervised transformer for population genetics, pretrained on 1000 Genomes data, that detects positive selection via haplotype-wise attention.

Generative single-cell foundation model trained on 100M+ transcriptomes that predicts how genetic perturbations reshape cell trajectories over time.

Small-molecule drug discovery foundation model covering ADMET, retrosynthesis, drug-target activity, and molecular optimization in a 2.6B checkpoint.

DNA foundation model using masked discrete diffusion to unify bidirectional sequence understanding and de novo generation in one architecture.

Contrastive model built on a genomic language model that predicts physical protein-protein interactions across a microbial proteome in linear time.

Graph-transformer foundation model pretrained on 3M protein pockets and 5M molecules as E(3)-equivariant graphs for protein-ligand representation.

Multimodal foundation model pretrained on ~500K unlabeled PubChem molecules that jointly predicts nine thermophysical properties of small molecules.