Paulo Verı́ssimo

Accurate Filtering of Privacy-Sensitive Information in Raw Genomic Data

The paper introduces a novel filtering method to identify privacy-sensitive nucleotides in genomic data, improving accuracy and reducing false positives compared to previous approaches.

Sensitivity Levels: Optimizing the Performance of Privacy Preserving DNA Alignment

This paper introduces a multi-level sensitivity classification for genomic variations to optimize privacy-preserving DNA alignment performance by adapting alignment algorithms to sensitivity levels.