Locating proteins in the cell using TargetP, SignalP and related tools

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Standard

Locating proteins in the cell using TargetP, SignalP and related tools. / Emanuelsson, Olof; Brunak, Søren; von Heijne, Gunnar; Nielsen, Henrik.

In: Nature Protocols (Online), Vol. 2, No. 4, 2007, p. 953-71.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Emanuelsson, O, Brunak, S, von Heijne, G & Nielsen, H 2007, 'Locating proteins in the cell using TargetP, SignalP and related tools', Nature Protocols (Online), vol. 2, no. 4, pp. 953-71. https://doi.org/10.1038/nprot.2007.131

APA

Emanuelsson, O., Brunak, S., von Heijne, G., & Nielsen, H. (2007). Locating proteins in the cell using TargetP, SignalP and related tools. Nature Protocols (Online), 2(4), 953-71. https://doi.org/10.1038/nprot.2007.131

Vancouver

Emanuelsson O, Brunak S, von Heijne G, Nielsen H. Locating proteins in the cell using TargetP, SignalP and related tools. Nature Protocols (Online). 2007;2(4):953-71. https://doi.org/10.1038/nprot.2007.131

Author

Emanuelsson, Olof ; Brunak, Søren ; von Heijne, Gunnar ; Nielsen, Henrik. / Locating proteins in the cell using TargetP, SignalP and related tools. In: Nature Protocols (Online). 2007 ; Vol. 2, No. 4. pp. 953-71.

Bibtex

@article{a2e64ca873dc495782f0566802dfdca6,
title = "Locating proteins in the cell using TargetP, SignalP and related tools",
abstract = "Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.",
keywords = "Amino Acid Motifs, Arabidopsis Proteins, Computational Biology, Protein Sorting Signals, Proteins, Sequence Analysis, Protein, Software",
author = "Olof Emanuelsson and S{\o}ren Brunak and {von Heijne}, Gunnar and Henrik Nielsen",
year = "2007",
doi = "10.1038/nprot.2007.131",
language = "English",
volume = "2",
pages = "953--71",
journal = "Nature Protocols (Online)",
issn = "1750-2799",
publisher = "nature publishing group",
number = "4",

}

RIS

TY - JOUR

T1 - Locating proteins in the cell using TargetP, SignalP and related tools

AU - Emanuelsson, Olof

AU - Brunak, Søren

AU - von Heijne, Gunnar

AU - Nielsen, Henrik

PY - 2007

Y1 - 2007

N2 - Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.

AB - Determining the subcellular localization of a protein is an important first step toward understanding its function. Here, we describe the properties of three well-known N-terminal sequence motifs directing proteins to the secretory pathway, mitochondria and chloroplasts, and sketch a brief history of methods to predict subcellular localization based on these sorting signals and other sequence properties. We then outline how to use a number of internet-accessible tools to arrive at a reliable subcellular localization prediction for eukaryotic and prokaryotic proteins. In particular, we provide detailed step-by-step instructions for the coupled use of the amino-acid sequence-based predictors TargetP, SignalP, ChloroP and TMHMM, which are all hosted at the Center for Biological Sequence Analysis, Technical University of Denmark. In addition, we describe and provide web references to other useful subcellular localization predictors. Finally, we discuss predictive performance measures in general and the performance of TargetP and SignalP in particular.

KW - Amino Acid Motifs

KW - Arabidopsis Proteins

KW - Computational Biology

KW - Protein Sorting Signals

KW - Proteins

KW - Sequence Analysis, Protein

KW - Software

U2 - 10.1038/nprot.2007.131

DO - 10.1038/nprot.2007.131

M3 - Journal article

C2 - 17446895

VL - 2

SP - 953

EP - 971

JO - Nature Protocols (Online)

JF - Nature Protocols (Online)

SN - 1750-2799

IS - 4

ER -

ID: 40804800