(Received: October 27, 2003; Accepted for publication: February 20, 2004; Published on Web: May 10, 2004)
In the domain of chemistry, many experimental data are being accumulated by combinatorial chemistry and high throughput screening (HTS) and so on. In order to obtain benefit information from these data, a lot of methodologies of chemometrics have been developed. Since usually these numerical data are represented as multi-dimensional arrays, traditional statistical software cannot handle these data directly. In this study, we developed data modeling software, which handles multi-dimensional arrays effectively. By using this software we are able to analyze multi-dimensional data. It is possible to understand the structure of multi-dimensional data by using graphical representation such as bar graph, line graph and so on. And the data modeling method, Multi-way PLS (partial least squares) and Kohonen neural network are available for the analysis of multi- dimensional data.
Keywords: Multi-dimensional data, Multi-way PLS, Kohonen neural network
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