Balaur Irina, Mazein Alexander, Saqi Mansoor, Lysenko Artem, Rawlings Christopher J, Auffray Charles
European Institute for Systems Biology and Medicine (EISBM), CIRI CNRS UMR 5308, CNRS-ENS-UCBL-INSERM, Lyon, France.
Rothamsted Research, Harpenden, West Common, Hertfordshire AL5 2JQ, UK.
Bioinformatics. 2017 Apr 1;33(7):1096-1098. doi: 10.1093/bioinformatics/btw731.
The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing.
The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/ . The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework .
Supplementary data are available at Bioinformatics online.
这项工作的目标是提供一个计算框架，用于探索来自Recon2人类代谢重建模型的数据。利用Neo4j图形数据库技术开发了高级用户访问功能，本文描述了关键特性，如网络数据的高效管理、针对特定任务的网络查询示例，以及查询结果如何转换回系统生物学标记语言（SBML）标准格式。基于Neo4j的代谢框架有助于探索高度连接且全面的人类代谢数据，并识别感兴趣的代谢子网。已开发了一个基于Java的解析器组件，将查询结果（以JSON格式提供）转换为SBML和SIF格式，以便于进一步探索结果、增强功能或共享网络。
基于Neo4j的代谢框架可从以下网址免费获取：https://diseaseknowledgebase.etriks.org/metabolic/browser/ 。为这项工作开发的Java代码文件可从以下网址获取：https://github.com/ibalaur/MetabolicFramework 。
补充数据可在《生物信息学》在线获取。
