Researchers at the Salk Institute have developed 'ShortStop,' an innovative machine learning framework designed to identify microproteins encoded by previously overlooked genomic regions. Microproteins, typically under 150 amino acids, have been challenging to detect with conventional methods due to their small size and coding within 'noncoding' DNA segments. ShortStop analyzes genomic data to predict biologically relevant microproteins, advancing insights into proteome complexity and opening new avenues for therapeutic target discovery, particularly demonstrated through lung cancer datasets.