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LOMETS: A local meta-threading-server for protein structure prediction
Open accessAbstract
We developed LOMETS, a local threading meta-server, for quick and automated predictions of protein tertiary structures and spatial constraints. Nine state-of-the-art threading programs are installed and run in a local computer cluster, which ensure the quick generation of initial threading alignments compared with traditional remote-server-based meta-servers. Consensus models are generated from the top predictions of the component-threading servers, which are at least 7% more accurate than the best individual servers based on TM-score at a t-test significance level of 0.1%. Moreover, side-chain and C-alpha (C(alpha)) contacts of 42 and 61% accuracy respectively, as well as long- and short-range distant maps, are automatically constructed from the threading alignments. These data can be easily used as constraints to guide the ab initio procedures such as TASSER for further protein tertiary structure modeling. The LOMETS server is freely available to the academic community at http://zhang.bioinformatics.ku.edu/LOMETS.
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Cited by
I-TASSER server for protein 3D structure prediction
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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-citationDeep‐learning contact‐map guided protein structure prediction in CASP13
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Self-citationProtein-Protein Complex Structure Predictions by Multimeric Threading and Template Recombination
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Self-citationLi, Y., Zhang, C., Bell, E. W., Yu, D., & Zhang, Y. (2019) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.25798 · Cited by 94
Self-citation
Metadata
- Authors
- Wu, S., & Zhang, Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-05
- Volume
- 35
- Issue
- 10
- Pages
- 3375-3382
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2126677834
- Cited by
- 778
- References
- 3
- FWCI
- 7.30
- Type
- journal article
- Language
- en
- Open access
- gold
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