Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Ernst Heydemann Strasse 8, D-18057 Rostock, Germany.
Cell Commun Signal. 2013 Nov 8;11:85. doi: 10.1186/1478-811X-11-85.
Small molecule effects can be represented by active signaling pathways within functional networks. Identifying these can help to design new strategies to utilize known small molecules, e.g. to trigger specific cellular transformations or to reposition known drugs.
We developed CellFateScout that uses the method of Latent Variables to turn differential high-throughput expression data and a functional network into a list of active signaling pathways. Applying it to Connectivity Map data, i.e., differential expression data describing small molecule effects, we then generated a Human Small Molecule Mechanisms Database. Finally, using a list of active signaling pathways as query, a similarity search can identify small molecules from the database that may trigger these pathways. We validated our approach systematically, using expression data of small molecule perturbations, yielding better predictions than popular bioinformatics tools.
CellFateScout can be used to select small molecules for their desired effects. The CellFateScout Cytoscape plugin, a tutorial and the Human Small Molecule Mechanisms Database are available at https://sourceforge.net/projects/cellfatescout/ under LGPLv2 license.
小分子的作用可以通过功能网络中的活跃信号通路来表示。识别这些信号通路可以帮助设计利用已知小分子的新策略,例如触发特定的细胞转化或重新定位已知药物。
我们开发了 CellFateScout,它使用潜在变量方法将差异高通量表达数据和功能网络转化为活跃信号通路列表。将其应用于 Connectivity Map 数据,即描述小分子作用的差异表达数据,我们生成了一个人类小分子机制数据库。最后,使用活跃信号通路列表作为查询,可以从数据库中识别可能触发这些通路的小分子。我们使用小分子扰动的表达数据系统地验证了我们的方法,其预测结果优于流行的生物信息学工具。
CellFateScout 可用于根据预期效果选择小分子。CellFateScout Cytoscape 插件、教程和人类小分子机制数据库可在 https://sourceforge.net/projects/cellfatescout/ 上根据 LGPLv2 许可证获得。