All Competitors

Meta-learning framework that transfers perturbation responses across cell lines, donors, and drugs from a few measured seed perturbations.

Large language model trained on functional genomics data to prioritize novel therapeutic targets from genome-wide CRISPR knockout screens.

Prime editing efficiency prediction from pegRNA sequence, with every biochemical step of the editing mechanism modeled as its own learned rate.

Prime editing efficiency prediction that quantifies per-pegRNA uncertainty, pairing a Dirichlet outcome model with conformal coverage guarantees.

Cas9 PAM preference prediction from protein sequence with an ESM-2 backbone, extending PAM annotation to 50,308 metagenome-mined orthologs.

Single-cell foundation model contrastively fine-tuned on genome-scale Perturb-seq data to separate perturbed from unperturbed transcriptomic states.

CRISPR/Cas9 off-target prediction that fine-tunes a DNA language model and gates in chromatin signal, reaching 0.550 PR-AUC on GUIDE-seq data.

Protein design model generating novel Cas9 and Cas12 genome-editing enzymes by Bayesian search over a classifier-separated sequence latent space.

CRISPR-Cas9 repair outcome prediction from microhomology and sequence features, with transfer learning that adapts to a new cell line from 50 samples.

CRISPR-Cas PAM specificity prediction directly from Cas protein sequence, plus computational evolution of Cas9 variants toward a chosen PAM.

CRISPR editing outcome prediction returning a probability over the near-full indel spectrum, with few-shot transfer to new cell types and to embryos.