CompBio is novel, mixed AI platform designed for multi-omics data analysis. This platform utilizes a combination of natural language processing (NLP), conditional probability analysis, and the extensive biological information contained in PubMed, including abstracts and full-text articles, to generate “knowledge maps” based on user-provided lists of multiomic entities. CompBio’s “holistic” analysis allows for the identification of both signal and noise components within a dataset with high accuracy and native traceability from enriched concepts to their source literature.The CompBio output is comprised of concepts identified as enriched in the user input list, which are clustered into themes with output significance reported. These themes represent non-redundant biological processes such as molecular pathways, physiological processes, cell types, and diseases, and are based on concept interrelationships in the associated literature. Theme annotation, the process of programmatically assigning concise titles to themes, is also performed in a contextually-aware manner acknowledging the relevant influence of neighboring themes and concepts on assignment of a title for a given theme. This approach rapidly identifies all available enriched biological knowledge in a biological dataset in a non-redundant and ontology-free manner, providing a powerful tool for the interpretation of multi-omics studies.