Ines F. Scheller

This study identifies a CDK4-selective molecular glue degrader, NE26394, using high-throughput proteomics, showing its efficacy in CDK4-dependent cancer models.

The paper identifies new CRBN neosubstrates using proteomic screening and machine learning, expanding the landscape of molecular glue degraders.

PROTRIDER detects protein expression outliers in proteomics data using conditional autoencoders, outperforming existing methods and revealing enrichments of pathogenic variants in outliers.

The paper introduces the Intron Jaccard Index to improve aberrant splicing detection in RNA-seq, reducing false positives while maintaining sensitivity in rare disease diagnostics.

Adding tandem mass tag proteomics to genome and transcriptome data resolved 22% of 121 unsolved suspected mitochondrial disease cases and surfaced two new disease genes.

FRASER detects aberrant splicing events in RNA-seq data, identifying pathogenic intron retention and improving sensitivity over z-score methods.