摘要
从代谢物、酶和生化反应信息重新构建正确的代谢网络是各项代谢网络相关研究非常关键的第一步。针对以往重构方法存在的数据难以及时更新、数据有冗余、获取数据慢等问题,本文采用分而治之的递归策略,提出了一种基于KEGG数据库自下而上重构全物种代谢网络的新方法。与以前的方法相比,本方法的优点在于:使用KEGG的Web服务获取数据,以保证数据的准确性和及时更新;依靠KEGG/PATHWAY库的数据选择机制选取数据,以保证构建网络的数据无冗余;整个方法基于Java实现,保证程序的跨平台通用性;通过构建MySQL本地数据库将远程数据本地化,大大降低数据读取的时耗。评估结果显示,该方法不仅能够保证重建网络数据的准确性和及时更新,而且有效地提高了多物种多次重构情况下的网络重构效率。
The high-quality network reconstruction from metabolites, enzymes and reactions is the first step for the study on metabolic networks. However, the previous reconstruction approaches have some disadvantages. For example, the data contains redundancy and could hardly be updated in time. Besides, the data retrieval is always time-consuming. In this paper, we propose a new bottom-up approach for the organism specific metabolic network reconstruction. The web service of KEC, G undertakes the data to be correct and up-to-date. The data selection mechanism of KEGG/PATHWAY ensures the reconstructed networks reliable. The whole approach is implemented using Java, which can be used on any platform independently. The MySQL database is deployed to map the remote data locally, which greatly shortens the elapsed time for the data retrieval. As is shown in the evaluation, this method can not only ensure the data for the network reconstruction is accurate and up-to-date, but also shorten the time in the case that many metabolic networks need reconstructing repeatedly.
出处
《计算机工程与科学》
CSCD
北大核心
2010年第8期104-107,111,共5页
Computer Engineering & Science
基金
国家自然科学基金资助项目(60773021,60603054)
