High dimensional biological data retrieval optimization with NoSQL technology.

ABSTRACT:

Background

High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data.

Results

In this paper we introduce a new data model better suited for high-dimensional data storage and querying, o

SUBMITTER: Wang S 

PROVIDER: S-EPMC4248814 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature