BioQuery-ASP: querying biomedical databases and ontologies using answer set programming

Abstract

Motivation and Objectives Storing biomedical data in various structured forms, like biomedical databases or ontologies, and at different locations have brought about many challenges for answering complex queries about the knowledge represented in these resources. For instance, here are two queries about some genes, drugs and diseases: “What are the drugs that treat the disease Depression and that do not target the gene ACYP1?”, “What are the 3 most similar drugs that target the gene DLG4?” One of the challenges of answering such complex queries is to represent the queries in a natural language and present the answers in an understandable form. Another challenge is to efficiently find answers to complex queries that require appropriate integration of relevant knowledge stored in different places and in various forms, and/or that require auxiliary definitions, such as, chains of drug-drug interactions, cliques of genes based on gene-gene relations, similarity/diversity of genes/drugs. Furthermore, once an answer is found for a complex query, the experts may need further explanations about the answer. We have developed novel computational methods and built a software system, called BioQuery-ASP, to handle all these challenges