Sugirthan Sivalingam

The paper uses long-read sequencing to characterize structural variants in 1,019 samples from the 1000 Genomes Project, identifying 167,291 sequence-resolved SVs and highlighting their genomic and functional implications.

The paper evaluates a structured diagnostic framework for ultra-rare diseases, showing improved genetic diagnoses and novel gene-disease associations using exome sequencing and AI tools.

GestaltMatcher improves diagnosis of ultra-rare genetic disorders by matching facial phenotypes to molecular diagnoses using a deep learning model trained on a large dataset of patient photographs.

This study identifies how PI3K/mTOR signaling and Trp53 loss determine the heterogeneity and excitability of BRAFV600E-induced brain tumors in mice.