RESUMO
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).
