Mapper: An intelligent restriction mapping tool

Abstract

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 out[put [post-processing module which enable 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/~nelson).