Simon Kasif

FusionInspector identifies and characterizes biologically relevant fusion transcripts from RNA-seq data in tumor and normal tissues using clustering and machine learning.

The paper identifies mediators of improved glycemia after gastric bypass surgery using a high-throughput mediation analysis method applied to plasma proteome and metabolome data.

The paper identifies a bias towards 3n - 1 length tandem repeats in multiple eukaryotic genomes, suggesting a potential evolutionary and disease-related genomic phenomenon.

The paper proposes a framework to optimize experimental design in biomedical research by prioritizing experiments based on potential information gain using AI and active learning.