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DeepLoc 2.1: multi-label membrane protein type prediction using protein language models.
Ødum, Marius Thrane; Teufel, Felix; Thumuluri, Vineet; Almagro Armenteros, José Juan; Johansen, Alexander Rosenberg; Winther, Ole; Nielsen, Henrik.
Afiliación
  • Ødum MT; Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.
  • Teufel F; Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark.
  • Thumuluri V; Digital Science & Innovation, Novo Nordisk A/S, 2760 Måløv, Denmark.
  • Almagro Armenteros JJ; University of California, San Diego, CA 92093, USA.
  • Johansen AR; Bristol Myers Squibb Company, Informatics and Predictive Sciences Research, Calle Isaac Newton 4, Sevilla 41092, Spain.
  • Winther O; Department of Computer Science, Stanford University, Stanford, CA 94305, USA.
  • Nielsen H; Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark.
Nucleic Acids Res ; 52(W1): W215-W220, 2024 Jul 05.
Article en En | MEDLINE | ID: mdl-38587188
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Proteínas de la Membrana Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article País de afiliación: Dinamarca Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Proteínas de la Membrana Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article País de afiliación: Dinamarca Pais de publicación: Reino Unido