Cole A. Deisseroth

The paper introduces SNACKKSS, a tool that integrates RNA-Seq data and biomedical literature to predict protein-inhibiting drugs, showing improved performance when combined with existing predictors.

This paper introduces PARMESAN, a tool that predicts drug-gene relationships using PubMed data, showing high accuracy for top-scoring predictions.

AMELIE 3 automatically reanalyzes undiagnosed Mendelian disease patients using new literature, achieving 80% diagnostic yield with 0.5-1 alerts per patient per year.

AMELIE 2 improves Mendelian disorder diagnosis by matching patient phenotypes and genotypes to primary literature, achieving high accuracy and efficiency.

AVADA automatically curates a database of pathogenic variants from full-text literature, outperforming existing methods and providing more variants than ClinVar.

ClinPhen automatically extracts and prioritizes patient phenotypes from medical records to improve genetic disease diagnosis efficiency.

Phrank improves Mendelian disease prioritization by ranking candidate genes or diseases based on phenotype similarity, outperforming existing methods in real patient exome data.

AMELIE automates Mendelian disorder diagnosis by analyzing literature and prioritizing candidate genes, achieving high diagnostic accuracy for singleton patients.