Juexiao Zhou

BioMINTREL enhances biological analysis by integrating cross-disciplinary methods, improving agreement with experts and uncovering new insights from existing data.

AutoBA is an AI agent that automates multi-omic analyses using large language models, offering adaptability and security across various sequencing and omics data types.

PPML-Omics is a privacy-preserving federated learning method that balances privacy protection and model utility across three omic data tasks.

The paper introduces AFS, a tool to revoke patients' private data from pre-trained models by auditing usage and purifying knowledge, tested across multiple tasks and datasets.

DeepTRs identifies tandem repeat variations directly from Nanopore reads using multi-modal conversion and deep learning, achieving high sensitivity, accuracy, and completeness.

AB-Gen uses reinforcement learning and a generative pre-trained Transformer to design antibody sequences with multiple desirable properties, improving success rates over traditional methods.

DeeReCT-TSS improves TSS annotation across cell types using DNA sequences and RNA-seq data, outperforming sequence-only methods and enabling cell-type-specific TSS identification.

DeeReCT-APA quantitatively predicts alternative polyadenylation site usage across genes using a deep learning model, outperforming existing methods in multiple tasks.