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SignalP 6.0 predicts all five types of signal peptides using protein language models. / Teufel, Felix; Almagro Armenteros, José Juan; Johansen, Alexander Rosenberg; Gíslason, Magnús Halldór; Pihl, Silas Irby; Tsirigos, Konstantinos D.; Winther, Ole; Brunak, Søren; von Heijne, Gunnar; Nielsen, Henrik.
I:
Nature Biotechnology, Bind 40, 2022, s. 1023-1025.
Publikation: Bidrag til tidsskrift › Kommentar/debat › Forskning
Harvard
Teufel, F, Almagro Armenteros, JJ, Johansen, AR, Gíslason, MH, Pihl, SI
, Tsirigos, KD, Winther, O, Brunak, S, von Heijne, G & Nielsen, H 2022, '
SignalP 6.0 predicts all five types of signal peptides using protein language models',
Nature Biotechnology, bind 40, s. 1023-1025.
https://doi.org/10.1038/s41587-021-01156-3
APA
Teufel, F., Almagro Armenteros, J. J., Johansen, A. R., Gíslason, M. H., Pihl, S. I.
, Tsirigos, K. D., Winther, O., Brunak, S., von Heijne, G., & Nielsen, H. (2022).
SignalP 6.0 predicts all five types of signal peptides using protein language models.
Nature Biotechnology,
40, 1023-1025.
https://doi.org/10.1038/s41587-021-01156-3
Vancouver
Teufel F, Almagro Armenteros JJ, Johansen AR, Gíslason MH, Pihl SI
, Tsirigos KD o.a.
SignalP 6.0 predicts all five types of signal peptides using protein language models.
Nature Biotechnology. 2022;40:1023-1025.
https://doi.org/10.1038/s41587-021-01156-3
Author
Teufel, Felix ; Almagro Armenteros, José Juan ; Johansen, Alexander Rosenberg ; Gíslason, Magnús Halldór ; Pihl, Silas Irby ; Tsirigos, Konstantinos D. ; Winther, Ole ; Brunak, Søren ; von Heijne, Gunnar ; Nielsen, Henrik. / SignalP 6.0 predicts all five types of signal peptides using protein language models. I: Nature Biotechnology. 2022 ; Bind 40. s. 1023-1025.
Bibtex
@article{3728c1fabbe2420da524ea4ab74e8bd3,
title = "SignalP 6.0 predicts all five types of signal peptides using protein language models",
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.",
author = "Felix Teufel and {Almagro Armenteros}, {Jos{\'e} Juan} and Johansen, {Alexander Rosenberg} and G{\'i}slason, {Magn{\'u}s Halld{\'o}r} and Pihl, {Silas Irby} and Tsirigos, {Konstantinos D.} and Ole Winther and S{\o}ren Brunak and {von Heijne}, Gunnar and Henrik Nielsen",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
doi = "10.1038/s41587-021-01156-3",
language = "English",
volume = "40",
pages = "1023--1025",
journal = "Nature Biotechnology",
issn = "1087-0156",
publisher = "nature publishing group",
}
RIS
TY - JOUR
T1 - SignalP 6.0 predicts all five types of signal peptides using protein language models
AU - Teufel, Felix
AU - Almagro Armenteros, José Juan
AU - Johansen, Alexander Rosenberg
AU - Gíslason, Magnús Halldór
AU - Pihl, Silas Irby
AU - Tsirigos, Konstantinos D.
AU - Winther, Ole
AU - Brunak, Søren
AU - von Heijne, Gunnar
AU - Nielsen, Henrik
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
U2 - 10.1038/s41587-021-01156-3
DO - 10.1038/s41587-021-01156-3
M3 - Comment/debate
C2 - 34980915
AN - SCOPUS:85122179157
VL - 40
SP - 1023
EP - 1025
JO - Nature Biotechnology
JF - Nature Biotechnology
SN - 1087-0156
ER -