The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Model Recognition Approach to the Prediction of All-Helical Membrane Protein Structure and Topology
Abstract
This paper describes a new method for the prediction of the secondary structure and topology of integral membrane proteins based on the recognition of topological models. The method employs a set of statistical tables (log likelihoods) complied from well-characterized membrane protein data, and a novel dynamic programming algorithm to recognize membrane topology models by expectation maximization. The statistical tables show definite biases toward certain amino acid species on the inside, middle, and outside of a cellular membrane. Using a set of 83 integral membrane protein sequences taken from a variety of bacterial, plant, and animal species, and a strict jackknifing procedure, where each protein (along with any detectable homologues) is removed from the training set used to calculate the tables before prediction, the method successfully predicted 64 of the 83 topologies, and of the 37 complex multispanning topologies 34 were predicted correctly.
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Citations
Cites
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
A new approach to protein fold recognition
Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221
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Cited by
Krogh, A., Larsson, B., von Heijne, G., & Sonnhammer, E. L. L. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.4315 · Cited by 12,654
The HMMTOP transmembrane topology prediction server
Tusnády, G. E., & Simon, I. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.9.849 · Cited by 1,907
Berge, K. E., Tian, H., Graf, G. A., Yu, L., Grishin, N. V., Schultz, J., Kwiterovich, P., Shan, B., Barnes, R., & Hobbs, H. H. (2000) · Science · doi:10.1126/science.290.5497.1771 · Cited by 1,648
Tusnády, G. E., & Simon, I. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2107 · Cited by 1,079
The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides
Tsirigos, K. D., Peters, C., Shu, N., Käll, L., & Elofsson, A. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv485 · Cited by 936
Metadata
- Authors
- Jones, D. T., Taylor, W. R., & Thornton, J. M.
- Venue
- Biochemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 1994-03-15
- Volume
- 33
- Issue
- 10
- Pages
- 3038-3049
- ISSN
- 0006-2960 (ISSN-L)
- 1520-4995
- OpenAlex
- W2089606003
- Cited by
- 779
- References
- 2
- FWCI
- 8.46
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Model Recognition Approach to the Prediction of All-Helical Membrane Protein Structure and Topology. https://app.cochat.ai/papers/10.1021/bi00176a037
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- Jones, D. T., Taylor, W. R., & Thornton, J. M. (1994). A Model Recognition Approach to the Prediction of All-Helical Membrane Protein Structure and Topology. Biochemistry. https://doi.org/10.1021/bi00176a037
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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.
