Generating Abstract Networks Using Multi-Relational Biological Data

被引：1

作者：

Caravelli, Paul ^{[1
]}

Beard, Mitch ^{[1
]}

Gopolan, Brian ^{[1
]}

Singh, Lisa ^{[1
]}

Hu, Zhang-Zhi ^{[2
]}

机构：

[1] Georgetown Univ, Dept Comp Sci, Washington, DC 20057 USA

[2] Georgetown Univ, Dept Oncol, Washington, DC 20057 USA

来源：

INFORMATION VISUALIZATION, IV 2009, PROCEEDINGS | 2009年

关键词：

D O I：

10.1109/IV.2009.73

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents an approach for visual exploration of groups in network data. We let users visually cluster nodes based on common semantic and relational features. We describe the clusters in the context of multi-relational protein data. Finally, we illustrate the clusters as composite nodes using a visual analytic tool and show how to create a meaningful abstracted protein network by connecting these composite nodes based on common membership or common attribute features.

引用

页码：331 / +

页数：2

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