An integrated model for visualizing biclusters from gene expression data and PPI networks

Q2 Medicine

In Silico Biology Pub Date : 2010-02-15 DOI:10.1145/1722024.1722052

Ahmet Emre Aladağ, C. Erten, Melih Sözdinler

引用次数: 2

Abstract

We provide a model to integrate the visualization of biclusters extracted from gene expresion data and the underlying PPI networks. Such an integration conveys the biologically relevant interconnection between these two structures inferred from biological experiments. We model the reliabilities of the structures using directed graphs with vertex and edge weights. The resulting graphs are drawn using appropriate weighted modifications of the algorithms necessary for the layered drawings of directed graphs. We provide applications of the proposed visualization model on the S. cerevisiae dataset.

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从基因表达数据和PPI网络中可视化双聚类的集成模型

我们提供了一个模型来整合从基因表达数据中提取的双聚类的可视化和潜在的PPI网络。这种整合传达了从生物学实验中推断出的这两种结构之间的生物学相关互连。我们用带顶点和边权的有向图来建模结构的可靠性。结果图是使用有向图的分层绘制所需的算法的适当加权修改绘制的。我们在S. cerevisiae数据集上提供了所提出的可视化模型的应用。

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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来源期刊

In Silico Biology Computer Science-Computational Theory and Mathematics

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.