Wuwei Tan

PISCO improves codon optimization by integrating protein structure and host-specific codon usage, enhancing solubility and expression.

This paper introduces an antibody language model (AbLM) to accelerate IgG screening and design for broad-spectrum antiviral therapy, achieving higher precision in predicting variant-resistant antibodies.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

The paper evaluates 23 imputation models for cross-cell type epigenomic data, finding quality assessment challenging due to distributional shifts, data availability, and redundant metrics.

The paper develops a multimodal deep learning model that combines 1D genome sequence and 3D chromatin structure to predict noncoding variant effects, outperforming sequence-only models.

The paper shows that polyadenylation of H3.1 mRNA displaces H3.3 from gene regulatory elements, leading to cell transformation and genomic instability.