Salvatore M, Shu N, Elofsson A
Science for Life Laboratory, Stockholm University, 171 21, Solna, Sweden.
Department of Biochemistry and Biophysics, Stockholm University, 106 91, Stockholm, Sweden.
Protein Sci. 2018 Jan;27(1):195-201. doi: 10.1002/pro.3297. Epub 2017 Oct 24.
SubCons is a recently developed method that predicts the subcellular localization of a protein. It combines predictions from four predictors using a Random Forest classifier. Here, we present the user-friendly web-interface implementation of SubCons. Starting from a protein sequence, the server rapidly predicts the subcellular localizations of an individual protein. In addition, the server accepts the submission of sets of proteins either by uploading the files or programmatically by using command line WSDL API scripts. This makes SubCons ideal for proteome wide analyses allowing the user to scan a whole proteome in few days. From the web page, it is also possible to download precalculated predictions for several eukaryotic organisms. To evaluate the performance of SubCons we present a benchmark of LocTree3 and SubCons using two recent mass-spectrometry based datasets of mouse and drosophila proteins. The server is available at http://subcons.bioinfo.se/.
SubCons是一种最近开发的预测蛋白质亚细胞定位的方法。它使用随机森林分类器结合了来自四个预测器的预测结果。在此,我们展示了SubCons用户友好的网络界面实现。从蛋白质序列开始,服务器能快速预测单个蛋白质的亚细胞定位。此外,服务器接受通过上传文件或以编程方式使用命令行WSDL API脚本提交的蛋白质组。这使得SubCons非常适合进行全蛋白质组分析,让用户能够在几天内扫描整个蛋白质组。从网页上,还可以下载针对几种真核生物的预先计算好的预测结果。为了评估SubCons的性能,我们使用基于小鼠和果蝇蛋白质的两个最新质谱数据集展示了LocTree3和SubCons的基准测试。该服务器可在http://subcons.bioinfo.se/获取。