The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
I‐TASSER: Fully automated protein structure prediction in CASP8
Open accessAbstract
The I‐TASSER algorithm for 3D protein structure prediction was tested in CASP8, with the procedure fully automated in both the Server and Human sections. The quality of the server models is close to that of human ones but the human predictions incorporate more diverse templates from other servers which improve the human predictions in some of the distant homology targets. For the first time, the sequence‐based contact predictions from machine learning techniques are found helpful for both template‐based modeling (TBM) and template‐free modeling (FM). In TBM, although the accuracy of the sequence based contact predictions is on average lower than that from template‐based ones, the novel contacts in the sequence‐based predictions, which are complementary to the threading templates in the weakly or unaligned regions, are important to improve the global and local packing in these regions. Moreover, the newly developed atomic structural refinement algorithm was tested in CASP8 and found to improve the hydrogen‐bonding networks and the overall TM‐score, which is mainly due to its ability of removing steric clashes so that the models can be generated from cluster centroids. Nevertheless, one of the major issues of the I‐TASSER pipeline is the model selection where the best models could not be appropriately recognized when the correct templates are detected only by the minority of the threading algorithms. There are also problems related with domain‐splitting and mirror image recognition which mainly influences the performance of I‐TASSER modeling in the FM‐based structure predictions. Proteins 2009. © 2009 Wiley‐Liss, Inc.
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
I-TASSER server for protein 3D structure prediction
Zhang, Y. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-40 · Cited by 5,124
Self-citationThe protein structure prediction problem could be solved using the current PDB library
Zhang, Y., & Skolnick, J. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407152101 · Cited by 297
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
Self-citation
Cited by
Kopec, K. O., Alva, V., & Lupas, A. N. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq326 · Cited by 212
Sagaram, U. S., Pandurangi, R., Kaur, J., Smith, T. J., & Shah, D. M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018550 · Cited by 185
Protein-Protein Complex Structure Predictions by Multimeric Threading and Template Recombination
Mukherjee, S., & Zhang, Y. (2011) · Structure · doi:10.1016/j.str.2011.04.006 · Cited by 174
Self-citationBussières, S., Cantin, L., Desbat, B., & Salesse, C. (2012) · Langmuir · doi:10.1021/la203896n · Cited by 20
Zhang, Y., Zhang, Z., Kagaya, Y., Terashi, G., Zhao, B., Xiong, Y., & Kihara, D. (2025) · Communications Biology · doi:10.1038/s42003-025-08783-5 · Cited by 19
Self-citationGraphGPSM: a global scoring model for protein structure using graph neural networks
He, G., Liu, J., Liu, D., & Zhang, G. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad219 · Cited by 16
Metadata
- Authors
- Zhang, Y.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2009-01
- Volume
- 77
- Issue
- S9
- Pages
- 100-113
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2110779321
- Cited by
- 421
- References
- 3
- FWCI
- 15.96
- Type
- journal article
- Language
- en
- Open access
- bronze
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
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.