Husen Muhammad Umer

The paper reanalyzes human tissue proteomics data using pangenome references to identify novel peptides and variants, demonstrating the effectiveness of proteogenomics approaches with pangenome data.

The paper introduces tools to generate proteogenomics databases using ENSEMBL resources, revealing non-canonical peptides in public datasets.

The paper introduces funMotifs, a framework to identify tissue-specific functional transcription factor motifs using genomic annotations and regulatory element activity scores, enabling variant analysis across multiple datasets.

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.