1. Главная
  2. Ресурсы
  3. Библиотечный поиск
SignalP 6.0 predictsall five types ofsignal peptides usingprotein languagemodels Felix TeufelJosé Juan Almagro ArmenterosAlexander Rosenberg Johansen2022 год

SignalP 6.0 predicts all five types of signal peptides using protein language models
статья из журнала

Полный текстСтраница публикацииПубликация в OpenAlex
Аннотация: Abstract Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data.
Год издания: 2022
Авторы: Felix Teufel, José Juan Almagro Armenteros, Alexander Rosenberg Johansen, Magnús Halldór Gíslason, Silas Irby Pihl, Konstantinos D. Tsirigos, Ole Winther, Søren Brunak, Gunnar von Heijne, Henrik Nielsen
Издательство: Nature Portfolio
Источник: Nature Biotechnology
Ключевые слова: Machine Learning in Bioinformatics, Genomics and Phylogenetic Studies, RNA and protein synthesis mechanisms
Другие ссылки: Nature Biotechnology (PDF)
Nature Biotechnology (HTML)
Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (PDF)
Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (HTML)
Repository for Publications and Research Data (ETH Zurich) (PDF)
Repository for Publications and Research Data (ETH Zurich) (HTML)
Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (HTML)
PubMed Central (HTML)
PubMed (HTML)