Fungal Bioinformatics Laboratory, Seoul National University, Seoul 151-921, Korea.
BMC Genomics. 2010 Feb 11;11:105. doi: 10.1186/1471-2164-11-105.
Fungi secrete various proteins that have diverse functions. Prediction of secretory proteins using only one program is unsatisfactory. To enhance prediction accuracy, we constructed Fungal Secretome Database (FSD).
A three-layer hierarchical identification rule based on nine prediction programs was used to identify putative secretory proteins in 158 fungal/oomycete genomes (208,883 proteins, 15.21% of the total proteome). The presence of putative effectors containing known host targeting signals such as RXLX [EDQ] and RXLR was investigated, presenting the degree of bias along with the species. The FSD's user-friendly interface provides summaries of prediction results and diverse web-based analysis functions through Favorite, a personalized repository.
The FSD can serve as an integrated platform supporting researches on secretory proteins in the fungal kingdom. All data and functions described in this study can be accessed on the FSD web site at http://fsd.snu.ac.kr/.
真菌分泌具有多种功能的各种蛋白质。仅使用一个程序预测分泌蛋白的效果并不理想。为了提高预测准确性,我们构建了真菌分泌组数据库(FSD)。
基于九个预测程序的三层分层识别规则,用于鉴定 158 种真菌/卵菌基因组(208833 种蛋白质,占总蛋白质组的 15.21%)中的推定分泌蛋白。研究了含有已知宿主靶向信号(如 RXLX[EDQ]和 RXLR)的推定效应子的存在情况,并显示了沿物种的偏倚程度。FSD 的用户友好界面通过 Favorite 提供了预测结果的摘要以及各种基于网络的分析功能,Favorite 是一个个性化的存储库。
FSD 可以作为一个集成平台,支持真菌王国分泌蛋白的研究。本研究中描述的所有数据和功能均可在 FSD 网站 http://fsd.snu.ac.kr/ 上访问。