PlasmoID: A P. falciparum Information Discovery Tool

Silico Biol. Pub Date : 1900-01-01 DOI:10.3233/ISB-2009-0403
Aditya Rao, S. Yeleswarapu, Gudladona Raghavendra, Rajgopal Srinivasan, Gopalakrishnan Bulusu
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引用次数: 5

Abstract

Plasmodium falciparum is the parasite responsible for more than 90% of deaths that occur due to malaria. Organization and mining of 'omic' (genomic, proteomic, transcriptomic, interactomic) data can improve our understanding of P. falciparum biology and help in the fight against malaria. PlasmoID (Plasmodium Information Discovery) is a tool developed for the dynamic exploration of the parasite's 'omic' landscape. Diverse computational and curated P. falciparum protein-protein interaction datasets, as well as binary relationships involving protein-small molecule entities, manually curated protein-protein relationships derived from the published literature and protein-protein interactions based on metabolic pathways are included in the PlasmoID database. The graphical user interface is designed as a plug-in to Cytoscape, an open-source network visualization tool. Important features of this plug-in include a synchronized tabular representation of any network loaded on the canvas, ability to find the shortest path between a pair of nodes in the database, search and expansion of entities from the database, and the ability to add new entities to the database through the interface. Malaria researchers can now seamlessly interrogate heterogeneous 'omic' datasets as well as add proprietary data to generate and visualize P. falciparum pathway and cell process network models. PlasmoID can be downloaded from http://pfalciparum.atc.tcs.com/PlasmoID.
PlasmoID:恶性疟原虫信息发现工具
恶性疟原虫是造成90%以上疟疾死亡的寄生虫。组织和挖掘“组学”(基因组学、蛋白质组学、转录组学、相互作用组学)数据可以提高我们对恶性疟原虫生物学的理解,并有助于防治疟疾。PlasmoID(疟原虫信息发现)是一种用于动态探索寄生虫“基因组”景观的工具。PlasmoID数据库包括多种计算和整理的恶性疟原虫蛋白质-蛋白质相互作用数据集,以及涉及蛋白质-小分子实体的二元关系,源自已发表文献的人工整理的蛋白质-蛋白质关系,以及基于代谢途径的蛋白质-蛋白质相互作用。图形用户界面被设计为Cytoscape的插件,这是一个开源的网络可视化工具。该插件的重要特性包括画布上加载的任何网络的同步表格表示、查找数据库中一对节点之间最短路径的能力、搜索和扩展数据库中的实体以及通过接口向数据库添加新实体的能力。疟疾研究人员现在可以无缝地查询异构的“组学”数据集,并添加专有数据来生成和可视化恶性疟原虫途径和细胞过程网络模型。PlasmoID可以从http://pfalciparum.atc.tcs.com/PlasmoID下载。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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