Designing Novel Queries for Analysing NoSQL Data of Gene-Disease Associations

Abstract

To precisely identify gene associated diseases has been an open area of research for biological scientists to ensure clinical and psychological symptoms and treatment for human diseases. Because whole Human Genome is defined now it is the next step to find all necessary possible factors from such a complex data set that cause gene mutations and hence lead inherited and/or non-inherited diseases. So our research implementation combines all important factors from different biomolecular data sources to make one integrated data set and defines new relationships among these factors for gene associated disease/s that were not present in existing platforms. This paper presents a novel query model for NoSQL data storage that can help researchers to visualise relationships among gene factors and two new factors termed as “causative factors” and “drugs/treatment” for associated diseases. Since no data source applies graphical querying for gene associated diseases, our proposed novel cypher query model can help researchers to deeply analyse data set and get results in an efficient manner. The proposed query model writes novel cypher queries for this research domain on a graphical data model implemented in neo4j, which is a NoSQL (Not Only Structured) database. Use of NoSQL database and NoSQL query language has overcome certain limitations of relational databases, the existing data platforms had to cope up with. This paper gives a new suitable data storage format and effective data search queries for large, complex, semi-structured and multi-dimensional gene associated diseases data set to efficiently define new relationships among factors format to open new horizons of research.