Abstract:
DeepLoc 2.0 is a popular web server for the prediction of protein subcellular localization and sorting signals. Here, we introduce DeepLoc 2.1, which additionally classifies the input proteins into the membrane protein types Transmembrane, Peripheral, Lipid-anchored and Soluble. Leveraging pre-trained transformer-based protein language models, the server utilizes a three-stage architecture for sequence-based, multi-label predictions. Comparative evaluations with other established tools on a test set of 4933 eukaryotic protein sequences, constructed following stringent homology partitioning, demonstrate state-of-the-art performance. Notably, DeepLoc 2.1 outperforms existing models, with the larger ProtT5 model exhibiting a marginal advantage over the ESM-1B model. The web server is available at https://services.healthtech.dtu.dk/services/DeepLoc-2.1.
摘要:
DeepLoc2.0是一个流行的网络服务器,用于预测蛋白质亚细胞定位和分选信号。这里,我们引入DeepLoc2.1,它还将输入蛋白分类为跨膜蛋白类型,外围设备,脂质锚定和可溶性。利用预先训练的基于变压器的蛋白质语言模型,服务器采用基于序列的三阶段架构,多标签预测。与其他已建立的工具对4933个真核蛋白质序列的测试集进行比较评估,在严格的同源性划分之后构建,展示最先进的表演。值得注意的是,DeepLoc2.1优于现有模型,与ESM-1B模型相比,更大的ProtT5模型表现出边际优势。Web服务器在https://services中可用。healthtech.dtu.dk/services/DeepLoc-2.1.