Data Management

Microarray experiments produce tremendous quantities of data: a single hybridization can generate a file containing millions of data points. In addition to this raw data, great amounts of information about the samples, their processing, and the hybridization of the arrays is generated. Managing this raw data as well as experimental process annotation is a huge task and an important consideration in the microarray process.

Raw Data

Storing
Retrieving

Databases can make organizing and retrieving of the raw data more efficient.

Experiment Annotation

Samples
Protocols

RNA extraction
Labeling
Hybridization
Analysis

Keeping track of experimental annotation is important for the analysis process as well as for meeting requirements for the publication of the data.