Mining to find the lipid interaction networks involved in Ovarian Cancers.

Rajaraman Kanagasabai, Kothandaraman Narasimhan, Hong-Sang Low, Wee Tiong Ang, Aaron Z Fernandis, Markus R Wenk, Mahesh A Choolani, Christopher J O Baker
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Abstract

The role of lipids in cancer during the genesis, progression and subsequent metastasis stages is increasingly discussed in the scientific literature. This information is discussed in a wide range of journals making it difficult for researchers to track the latest developments. A comprehensive assessment and translation of the lipidome of ovarian cancer, originating from literature, has yet to be made. We illustrate the deployment of semantic technologies; lipid ontology and text mining, in the aggregation and coordination of lipid literature. We provide the first report on the roles and types of lipids involved in ovarian cancer based on the mining of literature and identify key lipid-protein interactions that may point to potential drug discovery targets.

Abstract Image

Abstract Image

寻找与卵巢癌相关的脂质相互作用网络。
在科学文献中,脂质在癌症的发生、发展和随后的转移阶段中的作用越来越多地被讨论。这些信息在各种各样的期刊上都有讨论,这使得研究人员很难追踪最新的发展。对卵巢癌脂质组的综合评估和翻译,源于文献,尚未作出。我们举例说明了语义技术的部署;脂质本体和文本挖掘,在脂质文献的聚集和协调。我们在文献挖掘的基础上提供了第一份关于脂质在卵巢癌中的作用和类型的报告,并确定了可能指向潜在药物发现靶点的关键脂质-蛋白质相互作用。
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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