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利用健康社交网络社区进行转化研究。

Leveraging health social networking communities in translational research.

机构信息

School of Informatics, Indiana University Purdue University, IN, USA.

出版信息

J Biomed Inform. 2011 Aug;44(4):536-44. doi: 10.1016/j.jbi.2011.01.010. Epub 2011 Feb 1.

Abstract

Health social networking communities are emerging resources for translational research. We have designed and implemented a framework called HyGen, which combines Semantic Web technologies, graph algorithms and user profiling to discover and prioritize novel associations across disciplines. This manuscript focuses on the key strategies developed to overcome the challenges in handling patient-generated content in Health social networking communities. Heuristic and quantitative evaluations were carried out in colorectal cancer. The results demonstrate the potential of our approach to bridge silos and to identify hidden links among clinical observations, drugs, genes and diseases. In Amyotrophic Lateral Sclerosis case studies, HyGen has identified 15 of the 20 published disease genes. Additionally, HyGen has highlighted new candidates for future investigations, as well as a scientifically meaningful connection between riluzole and alcohol abuse.

摘要

健康社交网络社区正在成为转化研究的新兴资源。我们设计并实现了一个名为 HyGen 的框架,该框架结合了语义网技术、图算法和用户分析来发现和优先考虑跨学科的新关联。本文重点介绍了为克服处理健康社交网络社区中患者生成内容的挑战而开发的关键策略。在结直肠癌中进行了启发式和定量评估。结果表明,我们的方法具有克服障碍和识别临床观察、药物、基因和疾病之间隐藏联系的潜力。在肌萎缩侧索硬化症的案例研究中,HyGen 确定了 20 个已发表疾病基因中的 15 个。此外,HyGen 还突出了未来研究的新候选对象,以及利鲁唑和酒精滥用之间具有科学意义的联系。

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