The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
I-TASSER server: new development for protein structure and function predictions
Open accessAbstract
The I-TASSER server (http://zhanglab.ccmb.med.umich.edu/I-TASSER) is an online resource for automated protein structure prediction and structure-based function annotation. In I-TASSER, structural templates are first recognized from the PDB using multiple threading alignment approaches. Full-length structure models are then constructed by iterative fragment assembly simulations. The functional insights are finally derived by matching the predicted structure models with known proteins in the function databases. Although the server has been widely used for various biological and biomedical investigations, numerous comments and suggestions have been reported from the user community. In this article, we summarize recent developments on the I-TASSER server, which were designed to address the requirements from the user community and to increase the accuracy of modeling predictions. Focuses have been made on the introduction of new methods for atomic-level structure refinement, local structure quality estimation and biological function annotations. We expect that these new developments will improve the quality of the I-TASSER server and further facilitate its use by the community for high-resolution structure and function prediction.
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The I-TASSER Suite: protein structure and function prediction
Yang, J., Yan, R., Roy, A., Xu, D., Poisson, J., & Zhang, Y. (2015) · Nature Methods · doi:10.1038/nmeth.3213 · Cited by 5,596
Self-citationI-TASSER server for protein 3D structure prediction
Zhang, Y. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-40 · Cited by 5,124
Self-citationProtein structure prediction: when is it useful?
Zhang, Y. (2009) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2009.02.005 · Cited by 277
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Cited by
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Single-sequence protein structure prediction using language models from deep learning
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Single-sequence protein structure prediction using a language model and deep learning
Chowdhury, R., Bouatta, N., Biswas, S., Floristean, C., Kharkar, A., Roy, K., Rochereau, C., Ahdritz, G., Zhang, J., Church, G. M., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01432-w · Cited by 455
Reliable identification of protein-protein interactions by crosslinking mass spectrometry
Lenz, S., Sinn, L. R., O’Reilly, F. J., Fischer, L., Wegner, F., & Rappsilber, J. (2021) · Nature Communications · doi:10.1038/s41467-021-23666-z · Cited by 157
Structural and functional characterization of the Spo11 core complex
Claeys Bouuaert, C., Tischfield, S. E., Pu, S., Mimitou, E. P., Arias-Palomo, E., Berger, J. M., & Keeney, S. (2021) · Nature Structural & Molecular Biology · doi:10.1038/s41594-020-00534-w · Cited by 87
Metadata
- Authors
- Yang, J., & Zhang, Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-04-16
- Volume
- 43
- Issue
- W1
- Pages
- W174-W181
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2094458603
- Cited by
- 2,515
- References
- 3
- FWCI
- 26.12
- Type
- journal article
- Language
- en
- Open access
- gold
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