Publication | Open Access
DeepLoc 2.1: multi-label membrane protein type prediction using protein language models
122
Citations
18
References
2024
Year
Structured PredictionEngineeringSubcellular LocalizationMolecular BiologyProtein Language ModelsData ScienceProteomicsDeeploc 2.0Deeploc 2.1Protein ModelingOmicsProtein Structure PredictionDeep LearningFunctional GenomicsBioinformaticsWeb ServerProtein BioinformaticsTarget PredictionOmics DatasetsComputational BiologySystems BiologyMedicine
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.
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