The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Neural Network Method for Identification of Prokaryotic and Eukaryotic Signal Peptides and Prediction of their Cleavage Sites
Open accessAbstract
We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied to genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server: .
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
Comparison of the predicted and observed secondary structure of T4 phage lysozyme
Matthews, B. W. (1975) · Biochimica et Biophysica Acta (BBA) - Protein Structure · doi:10.1016/0005-2795(75)90109-9 · Cited by 5,399
Cited by
Improved Prediction of Signal Peptides: SignalP 3.0
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
Self-citationSupport vector machine approach for protein subcellular localization prediction
Hua, S., & Sun, Z. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.8.721 · Cited by 854
Machine learning approaches for the prediction of signal peptides and other protein sorting signals
Nielsen, H., Brunak, S., & von Heijne, G. (1999) · Protein Engineering, Design and Selection · doi:10.1093/protein/12.1.3 · Cited by 608
Self-citationProtein interaction mapping: A Drosophila case study
Formstecher, E., Aresta, S., Collura, V., Hamburger, A., Meil, A., Trehin, A., Reverdy, C., Betin, V., Maire, S., Brun, C., et al. (2005) · Genome Research · doi:10.1101/gr.2659105 · Cited by 542
Couillault, C., Pujol, N., Reboul, J., Sabatier, L., Guichou, J.-F., Kohara, Y., & Ewbank, J. J. (2004) · Nature Immunology · doi:10.1038/ni1060 · Cited by 478
Metadata
- Authors
- Nielsen, H., Engelbrecht, J., Brunak, S., & Heijne, G. V.
- Venue
- International Journal of Neural Systems
- Publisher
- World Scientific Pub Co Pte Lt
- Published
- 1997-10
- Volume
- 08
- Issue
- 05n06
- Pages
- 581-599
- ISSN
- 0129-0657 (ISSN-L)
- 1793-6462
- OpenAlex
- W2148622452
- Cited by
- 700
- References
- 2
- FWCI
- 2.59
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Neural Network Method for Identification of Prokaryotic and Eukaryotic Signal Peptides and Prediction of their Cleavage Sites. https://app.cochat.ai/papers/10.1142/s0129065797000537
- The paper
- Nielsen, H., Engelbrecht, J., Brunak, S., & Heijne, G. V. (1997). A Neural Network Method for Identification of Prokaryotic and Eukaryotic Signal Peptides and Prediction of their Cleavage Sites. International Journal of Neural Systems. https://doi.org/10.1142/s0129065797000537
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
