Inglehart J A, Nelson P C, Zou Y
Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, University of Illinois at Chicago, 60607-7053, USA.
Bioinformatics. 1998;14(2):101-11. doi: 10.1093/bioinformatics/14.2.101.
To determine the most powerful artificial intelligence techniques for automated restriction mapping, and use them to create a powerful multiple-enzyme restriction mapping tool.
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.
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.
确定用于自动限制酶切图谱分析的最强大人工智能技术，并利用这些技术创建一个强大的多酶切限制酶切图谱工具。
最有效的搜索引擎采用模型驱动的穷举搜索以及基于普拉特分离理论的一种二元逻辑剪枝形式。进一步的实验促成了一个显著加快搜索速度的输入预处理模块和一个能让用户分析大型解集并降低其表面复杂性的输出后处理模块的开发。
通过选择“软件”选项，可从我们的网站（http://www.ai.eecs.uic.edu）下载所得工具Mapper的可执行版本。
