Integrated web visualizations for protein-protein interaction databases.
Integrated web visualizations for protein-protein interaction databases.
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DOI：
10.1186/s12859-015-0615-z
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发表时间：
2015-06-16
影响因子：
3
通讯作者：
Holzinger A
中科院分区：
文献类型：
--
作者：
Jeanquartier F;Jean-Quartier C;Holzinger A
了解生命系统对于治疗疾病至关重要。为了实现这一任务，我们必须了解基于蛋白质-蛋白质相互作用的生物网络。生物信息学已经提出了大量的数据库和工具，支持分析师在综合水平上探索蛋白质-蛋白质相互作用的知识发现。它们提供了预测和相关性，为未来的实验研究指明了可能性，并填补了空白，以完成生物化学过程的图景。有许多庞大的蛋白质-蛋白质相互作用数据库用于深入了解系统生物学的许多问题。许多计算资源将相互作用数据与分子背景的附加信息相结合。然而，生物信息学资源的多样性对理解的目标构成了障碍。我们提出了一个调查的数据库，使蛋白质网络的可视化分析。我们从N =53个支持可视化的资源中选择了M =10个，并根据以下标准进行了测试：互操作性，数据集成，可能的交互量，数据可视化质量和数据覆盖率。该研究揭示了可用性，可视化功能和质量以及交互量的差异。StringDB是推荐的首选。CPDB提供全面的数据集，IntAct允许用户更改网络布局。综合比较表可通过网络获得。补充表可在http://tinyurl.com/PPI-DB-Comparison-2015上查阅。只有一些具有图形可视化功能的网络资源才能成功地应用于蛋白质相互作用的交互式可视化分析。研究结果强调了进一步增强生化分析工具中可视化集成的必要性。确定的挑战是数据的全面性，信心，互动功能和可视化成熟。
Understanding living systems is crucial for curing diseases. To achieve this task we have to understand biological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of databases and tools that support analysts in exploring protein-protein interactions on an integrated level for knowledge discovery. They provide predictions and correlations, indicate possibilities for future experimental research and fill the gaps to complete the picture of biochemical processes. There are numerous and huge databases of protein-protein interactions used to gain insights into answering some of the many questions of systems biology. Many computational resources integrate interaction data with additional information on molecular background. However, the vast number of diverse Bioinformatics resources poses an obstacle to the goal of understanding. We present a survey of databases that enable the visual analysis of protein networks. We selected M =10 out of N =53 resources supporting visualization, and we tested against the following set of criteria: interoperability, data integration, quantity of possible interactions, data visualization quality and data coverage. The study reveals differences in usability, visualization features and quality as well as the quantity of interactions. StringDB is the recommended first choice. CPDB presents a comprehensive dataset and IntAct lets the user change the network layout. A comprehensive comparison table is available via web. The supplementary table can be accessed on http://tinyurl.com/PPI-DB-Comparison-2015. Only some web resources featuring graph visualization can be successfully applied to interactive visual analysis of protein-protein interaction. Study results underline the necessity for further enhancements of visualization integration in biochemical analysis tools. Identified challenges are data comprehensiveness, confidence, interactive feature and visualization maturing.
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影响因子：
14.9
作者：
Chatr-Aryamontri A;Breitkreutz BJ;Heinicke S;Boucher L;Winter A;Stark C;Nixon J;Ramage L;Kolas N;O'Donnell L;Reguly T;Breitkreutz A;Sellam A;Chen D;Chang C;Rust J;Livstone M;Oughtred R;Dolinski K;Tyers M
通讯作者：
Tyers M
影响因子：
14.9
作者：
Franceschini A;Szklarczyk D;Frankild S;Kuhn M;Simonovic M;Roth A;Lin J;Minguez P;Bork P;von Mering C;Jensen LJ
通讯作者：
Jensen LJ
影响因子：
3
作者：
Agapito G;Guzzi PH;Cannataro M
通讯作者：
Cannataro M
影响因子：
3
作者：
Holzinger A;Dehmer M;Jurisica I
通讯作者：
Jurisica I
影响因子：
14.9
作者：
Bader GD;Cary MP;Sander C
通讯作者：
Sander C