All Competitors

Digital hematopathology foundation model unifying blood-cell detection, classification, segmentation, and visual question answering.

Hierarchical DNA foundation model that co-trains a dynamic token-merging tokenizer with latent Transformers to match genomic information density.

Pretrained language model for 3D molecule generation in protein pockets, unifying de novo and fragment-based drug design in one multi-task framework.

Guided discrete diffusion model for antibody lead optimization, conditioning sequence design on the seed binder's CDR canonical backbone conformation.

Retrieval-augmented protein encoders that fuse homologous sequences into a single-pass transformer for variant effect and contact prediction.

Histopathology model predicting TP53 mutation status, TP53 RNA expression, and tumour taxonomy from H&E whole-slide images across 32 solid cancers.

Self-supervised Siamese network for cryo-electron tomography, enabling zero-shot denoising, segmentation, and macromolecule detection in tomograms.

Spectral prediction model for modified peptides, forecasting fragment-ion intensities and retention time with zero-shot generalization to unseen PTMs.

Multimodal conversational LLM for metabolite analysis, fusing a molecular-graph GNN and molecular-image CNN with a Vicuna-13B language backbone.

Denoising diffusion bridge model for peptide binder design that generates ligand surfaces and backbones complementary to a target receptor surface.

Equivariant diffusion model that converts peptide binders into drug-like small molecules, generating peptidomimetics inside the target protein pocket.

Protein dynamics model that samples conformational ensembles autoregressively at slow and fast timescales, generalizing zero-shot to unseen proteins.

Pathology foundation model that fuses global patch and cell-level tokens via joint-weighted attention pooling for H&E-based biomarker detection.

Genomics foundation model that unifies sequence-to-function prediction, DNA language modeling, and generative regulatory design in one backbone.

Single-cell latent diffusion model fine-tuned on 14.5 million CD4+ T cells to simulate transcriptomic effects of single-gene perturbations.

Digital pathology foundation models from PathAI, spanning a 22M-parameter variant and a 1.1B-parameter flagship trained on 551K whole-slide images.

Multi-target drug discovery framework pairing a diffusion-transformer generator with evolutionary latent-space search and synthesis-aware scoring.

Latent diffusion model for generating single-cell gene expression profiles, pairing a permutation-invariant autoencoder with a diffusion transformer.

Transformer foundation model for single-cell ATAC-seq that embeds both cells and cis-regulatory elements for annotation and batch correction.

Antibody language model pretrained only on CDR-H3 loops, giving embeddings for immune repertoire analysis and antibody sequence classification.

Hierarchical transformer with 1.2 billion parameters that predicts personalized gene expression from diploid genomes for variant effect prediction.

Histopathology foundation model extracting general-purpose features from H&E patches by distilling the UNI, Phikon, and CONCH pathology encoders.

Antibody language model adapted on paired heavy and light chains, using CDR-focused masking to sharpen embeddings for binding affinity prediction.