All Competitors

Self-supervised foundation model for continuous glucose monitoring, with dual streams separating slow physiological state from transient events.

Zebrafish sequence-to-function model predicting cell-type-specific gene expression from DNA sequence across embryonic development.

Diffusion transformer for virtual tissue synthesis, generating H&E histopathology patches conditioned on spatial gene expression and morphology.

Genetically aligned foundation model for blood smear cytology that links single-cell morphology to the chromosomal aberrations behind AML and APL.

Cell world model pretrained on a 2.4M-cell mouse embryonic atlas, predicting one-step transcriptional state transitions and perturbation response.

Protein language model trained on roughly 2.8 billion sequences, forming the representation core of Biohub's world model of protein biology.

Structure-prediction and design engine that turns ESMC sequence representations into all-atom 3D structures of proteins and biomolecular complexes.

Flow-matching framework that translates omics signatures across biological domains, such as mouse to human transcriptomics, without paired samples.

Generative model that reconstructs single-cell spatial coordinates from scRNA-seq guided by spatial transcriptomics, without cell-type labels.

Hyperbolic protein language model for alignment-free phylogenetic inference, turning ESM2-650M embeddings into distance matrices for tree placement.

700M-parameter DNA language model pretrained on the rice pangenome, serving as a reusable base model for crop genomics and molecular breeding.

Lung pathology foundation model adapted from Virchow2 on whole-slide images, validated across 32 tasks spanning the lung diagnostic workflow.

Contrastive promoter-protein pretraining that aligns bacterial promoters with their encoded proteins to learn regulatory genomics representations.

Variant effect predictor pairing a protein language model with family-specific evolutionary constraints to score stability, binding, and epistasis.

Dirichlet flow-matching model for protein design that generates family-aware sequences from ancestral-reconstruction priors, not random noise.

Mixture-of-Experts genomic foundation model for the human microbiome, with 4.7B parameters pretrained on bacterial, archaeal, and phage genomes.

RNA language model that predicts secondary structure of internal ribosome entry sites from sequence alone, trained on roughly 50,000 IRES sequences.

Codon-level mRNA language model adapted from ESM-2 650M by swapping amino-acid tokens for codon tokens, transferring protein knowledge to mRNA tasks.

Spatial transcriptomics foundation model for the tumor microenvironment, giving TME-aware embeddings and in silico perturbation from one checkpoint.

Metabolomic foundation model pretrained on UK Biobank NMR metabolite profiles, reused with a frozen backbone for aging, subtyping, and disease risk.

Promptable DNA language model that generates multi-kilobase plasmid sequences from plain-language component specs, refined with verifiable rewards.

Protein structure prediction and binder design in a single generative step, replacing AlphaFold3's iterative diffusion sampling with one forward pass.

Multimodal framework that detects and localizes DNA lesions from native nanopore signal, built on the damage-aware LesionBERT foundation model.

SE(3)-invariant masked autoencoder that learns protein fold representations from AlphaFold-DB structures, supporting zero-shot fold classification.