首页> 外文会议>11th IEEE International Conference on Data Mining Workshops >BioGraph: Knowledge Discovery and Exploration in the Biomedical Domain
【24h】

BioGraph: Knowledge Discovery and Exploration in the Biomedical Domain

机译:BioGraph:生物医学领域的知识发现与探索

获取原文
获取原文并翻译 | 示例

摘要

We present a data integration and data mining platform, called BioGraph, for knowledge discovery in the biomedical domain. BioGraph allows for the automated formulation of comprehensible functional hypotheses relating a concepts to targets. A typical setting in which BioGraph can assist, is gene prioritization. That is, given the researcher's interest in a certain disease, predict those genes that are most likely of being involved in this disease. Our system is based on cutting-edge graph and network mining techniques, adapted to specific demands and properties of data and researchers in the Biomedical domain. The basis is constructed by the integration of heterogeneous biomedical knowledge bases. On this unified network BioGraph provides literature supported indirect functional relations. By assessing the plausibility and specificity of these hypothetical functional paths, the unsupervised methodology is capable of appraising and ranking of research targets, without requiring prior domain knowledge from the user. BioGraph is implemented as a web service and is available at: www.biograph.be.
机译:我们提出了一个称为BioGraph的数据集成和数据挖掘平台,用于生物医学领域的知识发现。 BioGraph允许自动制定将概念与目标联系起来的可理解功能假设。 BioGraph可以协助的典型设置是基因优先排序。也就是说,考虑到研究人员对某种疾病的兴趣,请预测最有可能参与该疾病的那些基因。我们的系统基于最先进的图形和网络挖掘技术,适用于生物医学领域的数据和研究人员的特定需求和属性。通过整合异构生物医学知识库构建基础。在这个统一的网络上,BioGraph提供了文献支持的间接功能关系。通过评估这些假设功能路径的合理性和特异性,无监督的方法能够评估研究目标并对其进行排名,而无需用户事先提供领域知识。 BioGraph是作为Web服务实现的,可从以下网站获得:www.biograph.be。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号