DeepLoc 2.1: multi-label membrane protein type prediction using protein language models

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Standard

DeepLoc 2.1 : multi-label membrane protein type prediction using protein language models. / Ødum, Marius Thrane; Teufel, Felix; Thumuluri, Vineet; Armenteros, José Juan Almagro; Johansen, Alexander Rosenberg; Winther, Ole; Nielsen, Henrik.

I: Nucleic Acids Research, Bind 52, Nr. W1, 2024, s. W215-W220.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Ødum, MT, Teufel, F, Thumuluri, V, Armenteros, JJA, Johansen, AR, Winther, O & Nielsen, H 2024, 'DeepLoc 2.1: multi-label membrane protein type prediction using protein language models', Nucleic Acids Research, bind 52, nr. W1, s. W215-W220. https://doi.org/10.1093/nar/gkae237

APA

Ødum, M. T., Teufel, F., Thumuluri, V., Armenteros, J. J. A., Johansen, A. R., Winther, O., & Nielsen, H. (2024). DeepLoc 2.1: multi-label membrane protein type prediction using protein language models. Nucleic Acids Research, 52(W1), W215-W220. https://doi.org/10.1093/nar/gkae237

Vancouver

Ødum MT, Teufel F, Thumuluri V, Armenteros JJA, Johansen AR, Winther O o.a. DeepLoc 2.1: multi-label membrane protein type prediction using protein language models. Nucleic Acids Research. 2024;52(W1):W215-W220. https://doi.org/10.1093/nar/gkae237

Author

Ødum, Marius Thrane ; Teufel, Felix ; Thumuluri, Vineet ; Armenteros, José Juan Almagro ; Johansen, Alexander Rosenberg ; Winther, Ole ; Nielsen, Henrik. / DeepLoc 2.1 : multi-label membrane protein type prediction using protein language models. I: Nucleic Acids Research. 2024 ; Bind 52, Nr. W1. s. W215-W220.

Bibtex

@article{51caaa47edec41bf9ba7fe17fe4331ce,
title = "DeepLoc 2.1: multi-label membrane protein type prediction using protein language models",
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.",
author = "{\O}dum, {Marius Thrane} and Felix Teufel and Vineet Thumuluri and Armenteros, {Jos{\'e} Juan Almagro} and Johansen, {Alexander Rosenberg} and Ole Winther and Henrik Nielsen",
note = "Publisher Copyright: {\textcopyright} 2024 The Author(s).",
year = "2024",
doi = "10.1093/nar/gkae237",
language = "English",
volume = "52",
pages = "W215--W220",
journal = "Nucleic Acids Research",
issn = "0305-1048",
publisher = "Oxford University Press",
number = "W1",

}

RIS

TY - JOUR

T1 - DeepLoc 2.1

T2 - multi-label membrane protein type prediction using protein language models

AU - Ødum, Marius Thrane

AU - Teufel, Felix

AU - Thumuluri, Vineet

AU - Armenteros, José Juan Almagro

AU - Johansen, Alexander Rosenberg

AU - Winther, Ole

AU - Nielsen, Henrik

N1 - Publisher Copyright: © 2024 The Author(s).

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

U2 - 10.1093/nar/gkae237

DO - 10.1093/nar/gkae237

M3 - Journal article

C2 - 38587188

AN - SCOPUS:85198056537

VL - 52

SP - W215-W220

JO - Nucleic Acids Research

JF - Nucleic Acids Research

SN - 0305-1048

IS - W1

ER -

ID: 399110403