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Automated biological pathway knowledge retrieval based on semantic web services composition and AI planning

机译:基于语义Web服务组合和AI规划的自动化生物途径知识检索

摘要

This paper presents the experience gained on semantic web service composition technique applied to the bioinformatics domain. Specifically, the approach presented here consists of knowledge retrieval perspective in biological pathway. Semantic web services, annotated with domain ontology are used to describe services for pathway knowledge retrieval for Kyoto Encyclopedia of Gene and Genomes (KEGG) database. Retrieving knowledge can be seen as high level goals and the tasks involved can be decomposed into subtask to achieve the specified goals. We execute the composition of service by treating composition as planning problem using Hierarchical Task Network (HTN) planning system based on Simple Hierarchical Order Planner 2 (SHOP2). The approach for plan (task) decomposition using SHOP2 is implemented in automated way. We investigate the effectiveness of this approach by applying real world scenario in pathway information retrieval for Lactococcus Lactis (L. lactis) organism where biologists need to find out the pathway description from the given specific gene of interest.
机译:本文介绍了在生物信息学领域应用语义Web服务组合技术的经验。具体而言,此处介绍的方法包括生物途径中的知识检索观点。带有域本体的语义Web服务用于描述京都基因和基因组百科全书(KEGG)数据库的路径知识检索服务。检索知识可以看作是高级目标,并且所涉及的任务可以分解为子任务以实现指定的目标。我们通过使用基于简单分层订单计划器2(SHOP2)的分层任务网络(HTN)计划系统将组合视为计划问题来执行服务组合。使用SHOP2进行计划(任务)分解的方法是自动实现的。我们通过将实际情况应用于乳酸乳球菌(L. lactis)生物的途径信息检索中来研究这种方法的有效性,生物学家需要生物学家从给定的特定目的基因中找出途径描述。

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  • 年度 2012
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  • 正文语种 {"code":"en","name":"English","id":9}
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