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Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis

机译:基于知识的专家系统以及用于多序列比对构建和分析的概念验证案例研究

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摘要

The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented.
机译:传统的生物信息学分析方法依赖于独立的,针对特定任务的服务和应用程序,使用不同的输入和输出格式,这些格式通常是特质的,并且通常不设计用于互操作。通常,此类分析是由专家进行的,他们会手动验证过程中每个步骤所获得的结果。如今,不断产生的生物信息学信息量意味着处理用于研究此信息的各种应用程序给研究人员带来了重大的数据管理和分析挑战。现在不可能手动分析所有这些信息,需要能够处理大规模异构数据以提取相关信息的新方法。我们回顾了最近集成专家系统的使用,旨在为生物信息学研究提供更有效的知识提取。描述了一种用于构建基于知识的专家系统的通用方法,重点放在非结构化信息管理体系结构UIMA上,UIMA为数据和流程管理提供了便利。还介绍了一个案例研究,涉及一个名为AlexSys的多重比对专家系统原型。

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