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Using neural networks for prediction of the subcellular location of proteins
Open accessAbstract
Neural networks have been trained to predict the subcellular location of proteins in prokaryotic or eukaryotic cells from their amino acid composition. For three possible subcellular locations in prokaryotic organisms a prediction accuracy of 81% can be achieved. Assigning a reliability index, 33% of the predictions can be made with an accuracy of 91%. For eukaryotic proteins (excluding plant sequences) an overall prediction accuracy of 66% for four locations was achieved, with 33% of the sequences being predicted with an accuracy of 82% or better. With the subcellular location restricting a protein's possible function, this method should be a useful tool for the systematic analysis of genome data and is available via a server on the world wide web.
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Cited by
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Dyrløv Bendtsen, J., Nielsen, H., von Heijne, G., & Brunak, S. (2004) · Journal of Molecular Biology · doi:10.1016/j.jmb.2004.05.028 · Cited by 6,350
Nakai, K., & Horton, P. (1999) · Trends in Biochemical Sciences · doi:10.1016/s0968-0004(98)01336-x · Cited by 2,181
Some remarks on protein attribute prediction and pseudo amino acid composition
Chou, K.-C. (2011) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.12.024 · Cited by 1,225
Yu, C., Lin, C., & Hwang, J. (2004) · Protein Science · doi:10.1110/ps.03479604 · Cited by 916
Support vector machine approach for protein subcellular localization prediction
Hua, S., & Sun, Z. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.8.721 · Cited by 854
Metadata
- Authors
- Reinhardt, A.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 1998-05-01
- Volume
- 26
- Issue
- 9
- Pages
- 2230-2236
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2025131366
- Cited by
- 596
- References
- 0
- FWCI
- 7.43
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Reinhardt, A. (1998). Using neural networks for prediction of the subcellular location of proteins. Nucleic Acids Research. https://doi.org/10.1093/nar/26.9.2230
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