Chuan R Y
Department of Computer Science, Monash University, Clayton, Vic, Australia.
Artif Intell Med. 1993 Oct;5(5):447-64. doi: 10.1016/0933-3657(93)90036-3.
Restriction mapping is an important computational problem in molecular biology, particularly in genetic engineering and DNA sequencing. It is different in that it is not only a purely computational problem but involves an interaction between experimental data collection procedures and the mapping algorithms. Consequently, the problem is loosely defined and in practice requires a flexible and versatile algorithm. We describe a framework for solving many restriction mapping problems in the constraint logic programming language CLP (R) which takes advantage of the declarative and powerful features of constraint logic programming. A CLP (R) algorithm is developed for solving a simple restriction mapping problem. The algorithm is the extended to handle more complex variations of restriction mapping such as fragments with errors, circular maps, multiple enzymes and partial digests. The mapping variants are integrated within the same framework and differ in the constraints required to define the kind of map consistency. Various search heuristics and control strategies to improve the search process are also incorporated as constraints.
限制性图谱分析是分子生物学中的一个重要计算问题,特别是在基因工程和DNA测序领域。它的不同之处在于,它不仅是一个纯粹的计算问题,还涉及实验数据收集过程与图谱算法之间的相互作用。因此,这个问题的定义比较宽松,在实践中需要一种灵活通用的算法。我们描述了一个在约束逻辑编程语言CLP(R)中解决许多限制性图谱分析问题的框架,该框架利用了约束逻辑编程的声明性和强大功能。开发了一种CLP(R)算法来解决一个简单的限制性图谱分析问题。该算法被扩展以处理限制性图谱分析更复杂的变体,如带有错误的片段、环状图谱、多种酶和部分酶切。这些图谱变体被整合在同一个框架内,并且在定义图谱一致性类型所需的约束方面有所不同。各种搜索启发式方法和控制策略也作为约束被纳入,以改进搜索过程。