A Cypher query based NoSQL data mining on protein datasets using Neo4j graph database

Graph data analysis is one of the upcoming methodologies in various niches of computer science. Traditionally for storing, retrieving and experimenting test data, researchers start with mysql database which is more approachable and easier to build their test experimentation platform. These test bed mysql databases will store data in the form of rows and columns, over which various SQL queries are performed. At times when the structure and size of dataset changed, these traditional mysql databases become inefficient in storing and retrieving of data. When the structure of dataset changes from row-column to graph representation, mysql database based querying and analysis become inefficient. The internal representation of data is changed to key-value pairs, more often the data in an unstructured format, which prompted the researchers to think about other databases which can achieve faster retrieval and mining over the dataset. This paper explores the approach of NoSql query design and analysis of different datasets, particularly a proteome-protein dataset over a renowned graph database, Neo4j. The mode of experiments involve the evaluation of NoSql query execution on datasets vary in the number of nodes and relationships between them. It also emphasises the process of mining large graphs with meaningful queries based on a NoSql Query language called Cypher.