All Competitors

SE(3)-equivariant chemical language model for pocket-based 3D molecule generation, used to design an HPK1 inhibitor with in vivo anti-tumor efficacy.

Protein-protein interaction predictor fusing evolutionary and structural embeddings to screen bacterial and host-pathogen proteomes in minutes.

Hierarchical transformer for virus discovery in metagenomes, classifying viral genomes across taxonomic ranks and flagging candidate novel lineages.

Chemical language model for fragment-based drug discovery, trained on all 62M ZINC-22 fragments. Samples 99.9% chemically valid fragment SMILES.

Predicts virtual single-cell spatial transcriptomics from H&E histology using frozen pathology foundation models and spot-level supervision.

De novo antibiotic design framework coupling a 6.4B-parameter protein language model with reinforcement learning to generate antimicrobial peptides.

Protein structure prediction from general-purpose transformer blocks and flow matching, with no MSAs, pair representations, or triangle attention.

Self-supervised EEG foundation model that encodes each electrode independently, so one frozen encoder serves any channel count or montage.

Pfam domain annotation with a graph neural network over AlphaFold2 residue-interaction graphs and ESM-2 embeddings, one model for all families.

Phylogeny-aware genomic language model scoring variant effects from whole-genome alignments and species trees across three evolutionary timescales.

Micronuclei instance segmentation for fluorescence microscopy, using an anchor-tuned Mask R-CNN to detect micronuclei and link them to parent nuclei.

Yeast sequence-to-expression model pretrained as a masked DNA language model on 165 fungal genomes, predicting RNA-seq coverage and variant effects.

Isoform-resolved variant effect prediction from DNA sequence, using graph attention over transcript splice structures across 30 human tissues.

Splice donor and acceptor site prediction from raw DNA, scoring every position of a 20 kb window with an ensemble of dilated residual CNNs.

DNA methylation foundation model that learns blood aging as a continuous ODE and prescribes sparse CpG edits for in-silico rejuvenation.

Parameter-efficient peptide representation model whose BiLSTM autoencoder keeps latent axes aligned with physicochemical and DFT-derived descriptors.

Yeast sequence-to-expression model predicting strand-specific RNA-seq coverage across a 5 kb multi-gene window at 10 bp resolution.

RNA secondary structure prediction that fuses base-pair priors from four orthogonal folding tools, reaching 0.709 F1 on cross-family bpRNA-new.

Single-cell foundation model domain-adapting Llama-3.1-8B on 1.3M gastric cancer cells with gene-family cell sentences instead of ranked-gene order.

Antibody optimization by guided sequence-structure diffusion over antibody-antigen complexes, steered by affinity oracles trained on lab assay data.

Sequence-only protein-protein interaction prediction at proteome scale. Each protein is embedded once, so a pair score compares two stored vectors.

Diploid de novo genome assembly that scores assembly-graph edges with a graph neural network and reconstructs phased haplotypes by beam search.

Neuro-oncology foundation model for brain tumor MRI, using distributionally robust pretraining for molecular subtyping and survival prediction.