Visualizing the Gene Ontology-Annotated Clusters of Co-expressed Genes: A Two-Design Study

IF 1.3 Q4 ENGINEERING, BIOMEDICAL

Computer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualization Pub Date : 2008-07-09 DOI:10.1109/MEDIVIS.2008.9

D. Fung, Seok-Hee Hong, Kai Xu, D. Hart

引用次数: 1

Abstract

In molecular biology, Gene Ontology (GO) has often been used for annotation and as a data mining dimension. A frequently performed step in microarray analytics is the clustering of co-expressed genes by their GO bioprocesses. Biological deductions are then made from the visual representation of the cluster pattern. Thus far, the question of how different representations of GO-annotated clusters affect biological interpretation and usability has not been investigated. In this paper, we evaluated two representations of GO-annotated clusters of co-expressed genes. Using a published cDNA microarray dataset, we tested the effect of each representation on biological interpretation. We also reported the results of the user evaluation conducted with bench biologists from different areas of expertise. Our study suggests that the bipartite graph may be more suitable for microarray analytics.

查看原文本刊更多论文

可视化基因本体-共表达基因的注释簇:一项双设计研究

在分子生物学中，基因本体(Gene Ontology, GO)常被用于标注和作为数据挖掘维度。微阵列分析中经常执行的步骤是通过氧化石墨烯生物过程对共表达基因进行聚类。然后从集群模式的视觉表现中进行生物推理。到目前为止，go注释集群的不同表示如何影响生物解释和可用性的问题尚未被调查。在本文中，我们评估了go注释的共表达基因簇的两种表示。使用已发表的cDNA微阵列数据集，我们测试了每种表达对生物解释的影响。我们还报告了与来自不同专业领域的实验室生物学家进行的用户评估的结果。我们的研究表明，二部图可能更适合于微阵列分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Computer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualization ENGINEERING, BIOMEDICAL-

CiteScore

2.80

自引率

6.20%

发文量

102

期刊介绍： Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization is an international journal whose main goals are to promote solutions of excellence for both imaging and visualization of biomedical data, and establish links among researchers, clinicians, the medical technology sector and end-users. The journal provides a comprehensive forum for discussion of the current state-of-the-art in the scientific fields related to imaging and visualization, including, but not limited to: Applications of Imaging and Visualization Computational Bio- imaging and Visualization Computer Aided Diagnosis, Surgery, Therapy and Treatment Data Processing and Analysis Devices for Imaging and Visualization Grid and High Performance Computing for Imaging and Visualization Human Perception in Imaging and Visualization Image Processing and Analysis Image-based Geometric Modelling Imaging and Visualization in Biomechanics Imaging and Visualization in Biomedical Engineering Medical Clinics Medical Imaging and Visualization Multi-modal Imaging and Visualization Multiscale Imaging and Visualization Scientific Visualization Software Development for Imaging and Visualization Telemedicine Systems and Applications Virtual Reality Visual Data Mining and Knowledge Discovery.