Visualization and Integrated Data Mining of Disparate Information
Description:
The volumes and diversity of information in the discovery, development, and business processes within the chemical and life sciences industries require new approaches for analysis. Traditional list- or spreadsheet-based methods are easily overwhelmed by large amounts of data. Furthermore, generating strong hypotheses and, just as importantly, ruling out weak ones, requires integration across different experimental and informational sources. We have developed a framework for this integration, in…
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Date:
May 11, 2001
Creator:
Saffer, Jeffrey D.; Albright, Cory L.; Calapristi, Augustin J.; Chen, Guang; Crow, Vernon L.; Decker, Scott D. et al.
Item Type:
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Partner:
UNT Libraries Government Documents Department