Lin Chung-Yen, Chen Chia-Ling, Cho Chi-Shiang, Wang Li-Ming, Chang Chia-Ming, Chen Pao-Yang, Lo Chen-Zen, Hsiung Chao A
Division of Biostatistics and Bioinformatics, National Health Research Institutes, #128, Sec. 2 Yaun-Chio-Yun Rd, Taipei 115, Taiwan.
Bioinformatics. 2005 Apr 1;21(7):1288-90. doi: 10.1093/bioinformatics/bti101. Epub 2004 Oct 28.
We implemented a statistical model into our protein interaction database for validation of two-hybrid assays of Helicobacter pylori, and prediction of putative protein interactions not yet discovered experimentally. To present the enormous amount of experimental and inferred protein interaction networking maps, the H.pylori Database of Protein Interactomes (hp-DPI) is developed with a succinct yet comprehensive visualization tool integrated with annotation from Genbank, GO, and KEGG. hp-DPI is first built with, but not limited to, H.pylori protein interactions and is expected to naturally include other organisms' protein interacting relationships in the future.
我们在蛋白质相互作用数据库中应用了一种统计模型,用于验证幽门螺杆菌的双杂交试验,并预测尚未通过实验发现的假定蛋白质相互作用。为了展示大量的实验性和推断性蛋白质相互作用网络图,我们开发了幽门螺杆菌蛋白质相互作用组数据库(hp-DPI),它集成了简洁而全面的可视化工具,并结合了来自Genbank、GO和KEGG的注释。hp-DPI最初构建时纳入了但不限于幽门螺杆菌的蛋白质相互作用,预计未来会自然地纳入其他生物体的蛋白质相互作用关系。