Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institute of Cardiovascular and Metabolic Disease, 1 avenue Jean Poulhès, 31432 Toulouse, France.
BMC Bioinformatics. 2013 Jul 24;14:235. doi: 10.1186/1471-2105-14-235.
Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases.
In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs. KUPNetViz focuses on the simplicity of its usage and the clarity of resulting networks by reducing and/or automating advanced functionalities present in other biological network visualization packages. In addition, it allows the extrapolation of biomolecule interactions across different species, leading to the formulations of new plausible hypotheses, adequate experiment design and to the suggestion of novel biological mechanisms. We demonstrate the value of KUPNetViz by two usage examples: the integration of calreticulin as a key player in a larger interaction network in renal graft rejection and the novel observation of the strong association of interleukin-6 with polycystic kidney disease.
The KUPNetViz is an interactive and flexible biological network visualization and exploration tool. It provides renal biologists with biological network snapshots of the complex integrated data of the KUPKB allowing the formulation of new hypotheses in a user friendly manner.
生物学领域的科学家们不断取得技术进步，已经从传统的单一组学方法转向多组学实验方法，这对生物信息学提出了挑战，需要其架起这座连接多层面信息的桥梁。肾脏生物学领域的研究也不例外。大量和/或高通量实验的结果，为肾脏疾病提供了丰富的信息，这些信息散落在网络上。为了解决这个问题，我们最近提出了 KUPKB，这是一个用于肾脏疾病的多组学数据存储库。
在本文中，我们描述了 KUPNetViz，这是一种生物图谱探索工具，通过可视化生物分子相互作用来探索 KUPKB 数据。KUPNetViz 允许将不同物种、肾脏位置和肾脏疾病的多层次实验数据整合到蛋白质-蛋白质相互作用网络中，并允许与生物学功能、生化途径和其他功能元素（如 miRNA）相关联。KUPNetViz 专注于其使用的简单性和网络的清晰度，通过减少和/或自动化其他生物网络可视化软件包中存在的高级功能来实现。此外，它还允许跨不同物种推断生物分子相互作用，从而形成新的合理假设、适当的实验设计，并提出新的生物学机制。我们通过两个使用示例展示了 KUPNetViz 的价值：将钙网蛋白整合到肾脏移植物排斥反应的更大相互作用网络中作为关键参与者，以及观察到白细胞介素-6 与多囊肾病之间的强烈关联。
KUPNetViz 是一种交互式和灵活的生物网络可视化和探索工具。它为肾脏生物学家提供了 KUPKB 复杂综合数据的生物网络快照，允许以用户友好的方式提出新的假设。
