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代谢途径数据库MetaCyc家族中的数据挖掘。

Data mining in the MetaCyc family of pathway databases.

作者信息

Karp Peter D, Paley Suzanne, Altman Tomer

机构信息

Bioinformatics Research Group, SRI International, Menlo Park, CA, USA.

出版信息

Methods Mol Biol. 2013;939:183-200. doi: 10.1007/978-1-62703-107-3_12.

Abstract

Pathway databases collect the bioreactions and molecular interactions that define the processes of life. The MetaCyc family of pathway databases consists of thousands of databases that were derived through computational inference of metabolic pathways from the MetaCyc pathway/genome database (PGDB). In some cases, these DBs underwent subsequent manual curation. Curated pathway DBs are now available for most of the major model organisms. Databases in the MetaCyc family are managed using the Pathway Tools software. This chapter presents methods for performing data mining on the MetaCyc family of pathway DBs. We discuss the major data access mechanisms for the family, which include data files in multiple formats; application programming interfaces (APIs) for the Lisp, Java, and Perl languages; and web services. We present an overview of the Pathway Tools schema, an understanding of which is needed to query the DBs. The chapter also presents several interactive data mining tools within Pathway Tools for performing omics data analysis.

摘要

通路数据库收集定义生命过程的生物反应和分子相互作用。MetaCyc通路数据库家族由数千个数据库组成,这些数据库是通过从MetaCyc通路/基因组数据库(PGDB)对代谢通路进行计算推断而衍生出来的。在某些情况下,这些数据库随后经过了人工整理。现在,大多数主要模式生物都有经过整理的通路数据库。MetaCyc家族中的数据库使用Pathway Tools软件进行管理。本章介绍了对MetaCyc通路数据库家族进行数据挖掘的方法。我们讨论了该家族的主要数据访问机制,包括多种格式的数据文件;针对Lisp、Java和Perl语言的应用程序编程接口(API);以及网络服务。我们概述了Pathway Tools模式,要查询数据库需要了解该模式。本章还介绍了Pathway Tools中用于进行组学数据分析的几个交互式数据挖掘工具。

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