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Mapper: an intelligent restriction mapping tool
J A Inglehart1, P C Nelson, Y Zou
1Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, University of Illinois at Chicago, 60607-7053, USA.
Motivation:
To determine the most powerful artificial intelligence techniques for automated restriction mapping, and use them to create a powerful multiple-enzyme restriction mapping tool.
Results:
The most effective search engine utilized model-driven exhaustive search and a form of binary logic pruning based on Pratt's separation theory. Additional experimentation led to the development of an input preprocessing module which significantly speeds up searches, and an output post-processing module which enables users to analyze large solution sets and reduce their apparent complexity.
Availability:
An executable version of the resultant tool, Mapper, can be downloaded from our Web site (http://www.ai.eecs.uic.edu) by selecting the 'Software' option.
Contact:
nelson@eecs.uic.edu (http://www.ai.eecs.uic.edu/ñelson).