Department of Chemistry, Tongji University, Shanghai 200092, China.
Nucleic Acids Res. 2013 Jul;41(Web Server issue):W441-7. doi: 10.1093/nar/gkt428. Epub 2013 May 31.
Knowledge of subcellular localizations (SCLs) of plant proteins relates to their functions and aids in understanding the regulation of biological processes at the cellular level. We present PlantLoc, a highly accurate and fast webserver for predicting the multi-label SCLs of plant proteins. The PlantLoc server has two innovative characters: building localization motif libraries by a recursive method without alignment and Gene Ontology information; and establishing simple architecture for rapidly and accurately identifying plant protein SCLs without a machine learning algorithm. PlantLoc provides predicted SCLs results, confidence estimates and which is the substantiality motif and where it is located on the sequence. PlantLoc achieved the highest accuracy (overall accuracy of 80.8%) of identification of plant protein SCLs as benchmarked by using a new test dataset compared other plant SCL prediction webservers. The ability of PlantLoc to predict multiple sites was also significantly higher than for any other webserver. The predicted substantiality motifs of queries also have great potential for analysis of relationships with protein functional regions. The PlantLoc server is available at http://cal.tongji.edu.cn/PlantLoc/.
植物蛋白的亚细胞定位（SCL）知识与其功能相关，并有助于理解细胞水平的生物过程的调控。我们提出了 PlantLoc，这是一个用于预测植物蛋白多标签 SCL 的高度准确和快速的网络服务器。PlantLoc 服务器具有两个创新特点：通过递归方法构建无比对和基因本体信息的定位基序库；以及建立简单的架构，无需机器学习算法即可快速准确地识别植物蛋白 SCL。PlantLoc 提供预测的 SCL 结果、置信度估计以及实质性基序及其在序列中的位置。与其他植物 SCL 预测网络服务器相比，使用新的测试数据集进行基准测试，PlantLoc 在识别植物蛋白 SCL 方面达到了最高的准确性（总体准确性为 80.8%）。PlantLoc 预测多个位点的能力也明显高于其他任何网络服务器。查询的预测实质性基序也非常有潜力用于分析与蛋白质功能区域的关系。PlantLoc 服务器可在 http://cal.tongji.edu.cn/PlantLoc/ 上获得。
