Heberle Henry, Carazzolle Marcelo Falsarella, Telles Guilherme P, Meirelles Gabriela Vaz, Minghim Rosane
University of São Paulo, Instituto de Ciências Matemáticas e de Computação, Av. Trabalhador São-carlense, 400, São Carlos-SP, Brazil.
University of Campinas, Institute of Biology, Av. Albert Einstein, 1251, Campinas-SP, Brazil.
BMC Bioinformatics. 2017 Sep 13;18(Suppl 10):395. doi: 10.1186/s12859-017-1787-5.
The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability.
Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB.
CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.
“组学”科学的出现通过对分子相互作用的高通量分析为当代生物学带来了新的视角，为蛋白质/基因功能以及生物途径的组织提供了新线索。生物分子相互作用网络或图谱是简单的抽象表示形式，其中细胞的组成部分（例如蛋白质、代谢物等）由节点表示，它们之间的相互作用由边表示。对数据进行适当的可视化对于理解此类网络至关重要，因为途径与细胞特定区域中发生的功能相关。力导向布局是一种根据网络拓扑绘制网络的重要且广泛使用的技术。将网络放置到细胞区室中有助于快速识别网络元素的位置，更具体地说，是其集中位置。目前，只有少数工具具备按细胞区室直观组织网络的能力。其中大多数无法处理大型且密集的网络。即使对于具有数百个节点的小型网络，现有工具在用户交互时也无法重新定位网络，从而限制了视觉探索能力。
在此，我们提出了CellNetVis，这是一个网络工具，可使用约束力导向布局算法在细胞图中轻松显示生物网络。该工具免费且开源。它最初是为综合相互作用组系统生成的网络设计的，也可用于来自其他数据库（如InnateDB）的网络。
CellNetVis已证明适用于在网络上对细胞的一致表示上对复杂网络进行动态研究，其功能在其他地方无法比拟。
