Karp P D, Paley S M
Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA.
Proc Int Conf Intell Syst Mol Biol. 1994;2:203-11.
The automatic generation of drawings of metabolic pathways is a challenging problem that depends intimately on exactly what information has been recorded for each pathway, and on how that information is encoded. The chief contributions of the paper are a minimized representation for biochemical pathways called the predecessor list, and inference procedures for converting the predecessor list into a pathway-graph representation that can serve as input to a pathway-drawing algorithm. The predecessor list has several advantages over the pathway graph, including its compactness and its lack of redundancy. The conversion between the two representations can be formulated as both a constraint-satisfaction problem and a logical inference problem, whose goal is to assign directions to reactions, and to determine which are the main chemical compounds in the reaction. We describe a set of production rules that solves this inference problem. We also present heuristics for inferring whether the exterior compounds that are substrates of reactions at the periphery of a pathway are side or main compounds. These techniques were evaluated on 18 metabolic pathways from the EcoCyc knowledge base.
代谢途径图的自动生成是一个具有挑战性的问题，它紧密依赖于为每个途径记录的具体信息，以及这些信息的编码方式。本文的主要贡献是一种用于生化途径的最小化表示形式，称为前驱列表，以及将前驱列表转换为途径图表示形式的推理过程，该表示形式可作为途径绘制算法的输入。与途径图相比，前驱列表有几个优点，包括其紧凑性和无冗余性。两种表示形式之间的转换可以被表述为一个约束满足问题和一个逻辑推理问题，其目标是为反应分配方向，并确定反应中的主要化合物。我们描述了一组解决此推理问题的产生式规则。我们还提出了启发式方法，用于推断途径外围反应的底物外部化合物是次要化合物还是主要化合物。这些技术在来自EcoCyc知识库的18条代谢途径上进行了评估。
