通过 TVNViewer 中的可视化实现动态网络分析。

Enabling dynamic network analysis through visualization in TVNViewer.

机构信息

Joint Carnegie Mellon, University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, PA, USA.

出版信息

BMC Bioinformatics. 2012 Aug 16;13:204. doi: 10.1186/1471-2105-13-204.

DOI:10.1186/1471-2105-13-204

PMID:22897913

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3447684/

Abstract

BACKGROUND

Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis.

RESULTS

In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets.

CONCLUSIONS

TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.

摘要

背景

许多生物过程是依赖于上下文或具有时间特异性的。因此，分子成分之间的关系随时间和环境而演变。虽然最先进的机器学习技术可以恢复这些网络，但探索和解释这些重新布线的行为具有挑战性。信息可视化在这种探索性分析中大放异彩，这促使了 TVNViewer（http://sailing.cs.cmu.edu/tvnviewer）的开发，这是一种用于动态网络分析的可视化工具。