Identifying high-priority proteins across the human diseasome using semantic similarity

Abstract

Knowledge of \"popular proteins\" has been a focus of multiple Human Proteome Organization (HUPO) initiatives and can guide the development of proteomics assays targeting important disease pathways. We report here an updated method to identify prioritized protein lists from the research literature, and apply it to catalog lists of important proteins across multiple cell types, sub-anatomical regions, and disease phenotypes of interest. We provide a systematic collection of popular proteins across 10,129 human diseases as defined by the Disease Ontology, 10,642 disease phenotypes defined by Human Phenotype Ontology, and 2,370 cellular pathways defined by Pathway Ontology. This strategy allows instant retrieval of popular proteins across the human \"diseasome\", and further allows reverse queries from protein to disease, enabling functional analysis of experimental protein lists using bibliometric annotations.