Yuying Yuan

This study combines manual annotation and deep learning to improve name entity recognition in biomedical texts, achieving high F1-scores for gene, variant, disease, and species entities.

Cancer SIGVAR is a tool for interpreting germline cancer variants using 21 and 48 criteria, achieving high consistency in classification across benchmark databases.

The paper presents the first high-quality chromosome-scale genome assembly of Amphicarpaea edgeworthii using PacBio, 10x Genomics, and Hi-C technologies.

This study reports two cases of maternal malignancies detected incidentally during noninvasive prenatal tests in Asian women, showing concordant genome disruption patterns between tumor samples and NIPT results.