Data mining of environmental stress tolerances on plants.
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| Title: | Data mining of environmental stress tolerances on plants. |
|---|---|
| Authors: | Richard S. Segall, Gauri S. Guha, Sarath A. Nonis |
| Source: | Kybernetes. Jan2008, Vol. 37 Issue 1, p127-148. 22p. |
| Subjects: | Data mining, Databases, Osmotic potential of plants, Cluster analysis (Statistics), Medical botany |
| Abstract: | Purpose - 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. Design/methodology/approach - 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. Findings - This paper illustrates that useful information about the effects of environmental stress tolerances (ESTs) on plants can be obtained by using data mining. Research limitations/implications - 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. Practical implications - 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. Originality/value - 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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