Guohui Chuai

AlphaCell simulates perturbation-induced cellular dynamics by addressing limitations in current models through three innovations: latent manifold rectification, biological reality reconstruction, and universal state transition.

The paper introduces CHOOSER, a foundation model-based framework for discovering CRISPR-Cas systems with self-processing pre-crRNA capability, identifying 11 novel homologs and validating one for functional use.

This study introduces STAMP, a novel method for genetic perturbation outcome prediction that improves accuracy across three subtasks and provides a benchmarking framework for evaluating models.

This study introduces TCRBagger, a weakly-supervised framework for peptide-TCR binding prediction to improve neo-epitope identification in tumor immunotherapy.

X-MOL uses large-scale pre-training on 1.1 billion molecules to improve molecular analysis tasks through fine-tuning, achieving state-of-the-art results in property prediction, reaction analysis, and molecule generation.

This paper introduces FL-QSAR, a federated learning framework for QSAR analysis, demonstrating its effectiveness in collaborative drug discovery while preserving privacy.

The paper re-analyzes WGS data from two studies to find that CRISPR off-target mutations include both SNVs and indels, challenging previous conclusions about their rarity.