Yujia A. Chan

The paper develops a modified AAV capsid that targets the human Transferrin Receptor to enhance gene delivery to the CNS, showing improved reporter expression and therapeutic potential for Gaucher disease.

The paper introduces Fit4Function, a machine learning approach to engineer AAV capsids with multiple traits, achieving high transduction efficiency and cross-species prediction.

This paper identifies AAV capsids that target specific proteins on the blood-brain barrier, enhancing CNS tropism and enabling predictable gene delivery vectors.

This paper introduces a systematic auditing framework to identify biases in machine learning applications in biology, showing that biases can hinder model generalizability and lead to poor performance when training data lacks sufficient signal.

The paper introduces a resource for tracking SARS-CoV-2 mutations by location, date, and gene, with case studies on RBD SNVs, diagnostic primer sensitivity, and lineage emergence.

The paper traces the origin of pangolin CoV genomes with a Spike RBD similar to SARS-CoV-2 to a single batch of smuggled pangolins and highlights the need for transparency in genome assembly pipelines.

The paper identifies molecular properties that determine oxidative stress resistance in bacteria by analyzing protein susceptibility to oxidation in Escherichia coli and Deinococcus radiodurans.

The paper identifies LY6A as a novel receptor for AAV-PHP.B vectors, enabling efficient gene delivery across the blood-brain barrier in mice.

This paper introduces a method for rapid genome recoding in Salmonella typhimurium by iteratively recombineering synthetic DNA, achieving the highest number of codon substitutions in a single organism.