Chao Wu

AnthOligo automates the design of oligonucleotides for genomic capture technologies by optimizing parameters like Tm and ΔG while minimizing primer dimers.

Phen2Gene prioritizes genes based on HPO terms for rare diseases, outperforming existing tools in speed and accuracy for clinical diagnosis.

The paper presents a machine learning classifier to identify true somatic variants from next-generation sequencing data, achieving high specificity and sensitivity with minimal uncertainty.

The paper introduces a disease-specific variant pathogenicity predictor trained on clinical sequencing data from cardiomyopathy, epilepsy, and RASopathies patients.

Phenoxome improves clinical exome variant prioritization by integrating phenotypic and genomic data, achieving high accuracy in identifying causative variants.