This paper seeks to present a complete set of graphical and numerical outputs of data mining performed for microarray databases of plant data as described in earlier research by the authors. A brief description of data mining is also presented, as well as a brief background of previous research.
The paper uses applications of data mining using SAS Enterprise Miner Version 4 for plant data from the Osmotic Stress Microarray Information Database (OSMID) that is available on the web for both normalized and log(2) transformed data.
This paper illustrates that useful information about the effects of environmental stress tolerances (ESTs) on plants can be obtained by using data mining.
Use of SAS Enterprise Miner was very effective for performing data mining of microarray databases with its modules of cluster analysis, decision trees, and descriptive and visual statistics.
The data used from the OSMID database are considered to be representative of those that could be used for biotech application such as the manufacture of plant‐made‐pharmaceuticals and genetically modified foods.
This paper contributes to the discussion on the use of data mining for microarray databases and specifically for studying the effects of ESTs on plants.
