Feature-based prediction of non-classical and leaderless protein secretion. Bendtsen, J. D., Jensen, L. J., Blom, N., Heijne, G. v., & Brunak, S. Protein Engineering Design and Selection, 17(4):349--356, April, 2004. ![Feature-based prediction of non-classical and leaderless protein secretion [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex We present a sequence-based method, SecretomeP, for the prediction of mammalian secretory proteins targeted to the non-classical secretory pathway, i.e. proteins without an N-terminal signal peptide. So far only a limited number of proteins have been shown experimentally to enter the non-classical secretory pathway. These are mainly fibroblast growth factors, interleukins and galectins found in the extracellular matrix. We have discovered that certain pathway-independent features are shared among secreted proteins. The method presented here is also capable of predicting (signal peptide-containing) secretory proteins where only the mature part of the protein has been annotated or cases where the signal peptide remains uncleaved. By scanning the entire human proteome we identified new proteins potentially undergoing non-classical secretion. Predictions can be made at http://www.cbs.dtu.dk/services/SecretomeP.
@article{bendtsen_feature-based_2004,
title = {Feature-based prediction of non-classical and leaderless protein secretion},
volume = {17},
issn = {1741-0126, 1741-0134},
url = {http://peds.oxfordjournals.org/content/17/4/349},
doi = {10.1093/protein/gzh037},
abstract = {We present a sequence-based method, SecretomeP, for the prediction of mammalian secretory proteins targeted to the non-classical secretory pathway, i.e. proteins without an N-terminal signal peptide. So far only a limited number of proteins have been shown experimentally to enter the non-classical secretory pathway. These are mainly fibroblast growth factors, interleukins and galectins found in the extracellular matrix. We have discovered that certain pathway-independent features are shared among secreted proteins. The method presented here is also capable of predicting (signal peptide-containing) secretory proteins where only the mature part of the protein has been annotated or cases where the signal peptide remains uncleaved. By scanning the entire human proteome we identified new proteins potentially undergoing non-classical secretion. Predictions can be made at http://www.cbs.dtu.dk/services/SecretomeP.},
language = {en},
number = {4},
urldate = {2015-05-20TZ},
journal = {Protein Engineering Design and Selection},
author = {Bendtsen, Jannick Dyrløv and Jensen, Lars Juhl and Blom, Nikolaj and Heijne, Gunnar von and Brunak, Søren},
month = apr,
year = {2004},
pmid = {15115854},
keywords = {extracellular, growth factor, hormone, neural network, secretome},
pages = {349--356}
}
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