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一个基因图谱专家系统。

A gene mapping expert system.

作者信息

Galland J, Skolnick M H

机构信息

Department of Medical Informatics, University of Utah, Salt Lake City 84108.

出版信息

Comput Biomed Res. 1990 Aug;23(4):297-309. doi: 10.1016/0010-4809(90)90023-6.

Abstract

Expert systems are now commonly developed to solve practical problems. Nevertheless, genetics has just begun to benefit from this new technology, since genetic expert systems are extremely rare and often purely experimental. A prototype for risk calculation in pedigrees was developed at the University of Utah, using a commercial frames/rules developmental shell (Intelligence Compiler), which runs on an IBM PC. When small data sets were used, the implementation functioned well, but it could not handle larger data sets. Performance became a major issue, with two possible solutions. The first possibility would have been to port the system to a more powerful machine, and the second would have been to use several different shells or languages, each efficiently representing a specific type of knowledge. Neither of these solutions was applicable in this case. From this experience, we learned that performance, portability, and modifiability were three major requirements for genetic expert systems. To achieve these goals, we implemented the gene mapping expert system GMES: (GMES is unrelated to the gene mapping system, GMS in Lisp combined with a frame/object shell (FROBS). We were able to efficiently represent, control, and optimize a gene mapping experiment, achieving portability by building GMES on top of a C-based version of Common Lisp. Lisp combined with the FROBS expert system shell permitted a declarative representation of each of the components of the experiment, resulting in a transplant specification of the problem within a maintainable system.

摘要

专家系统如今通常被开发用于解决实际问题。然而,遗传学才刚刚开始从这项新技术中受益,因为遗传专家系统极为罕见,且往往纯粹是实验性的。犹他大学开发了一种用于系谱风险计算的原型系统,使用了一种商业框架/规则开发工具(智能编译器),该工具运行在IBM个人电脑上。当使用小数据集时,该系统运行良好,但无法处理更大的数据集。性能成为了一个主要问题,有两种可能的解决方案。第一种可能是将系统移植到更强大的机器上,第二种可能是使用几种不同的工具或语言,每种工具或语言都能有效地表示特定类型的知识。但在这种情况下,这两种解决方案都不适用。从这次经历中,我们了解到性能、可移植性和可修改性是遗传专家系统的三个主要要求。为了实现这些目标,我们实现了基因图谱专家系统GMES:(GMES与基因图谱系统无关,Lisp中的GMS与框架/对象工具FROBS相结合)。我们能够有效地表示、控制和优化基因图谱实验,通过在基于C的通用Lisp版本之上构建GMES实现了可移植性。Lisp与FROBS专家系统工具相结合,允许对实验的每个组件进行声明式表示,从而在一个可维护的系统中实现问题的移植规范。

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