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SAXSTER specifications


Unique identifier OMICS_10457
Interface Web user interface
Restrictions to use None
Input data The input to the server includes a query sequence and a set of SAXS raw data.
Computer skills Basic
Stability Stable
Maintained Yes


  • person_outline Yang Zhang

Publication for SAXSTER

SAXSTER citations


Structural and molecular comparison of bacterial and eukaryotic trigger factors

Sci Rep
PMCID: 5587573
PMID: 28878399
DOI: 10.1038/s41598-017-10625-2

[…] DAMMIF and then averaged with DAMAVER . As a last refinement step, the damstart model generated with DAMAVER was refined with one cycle in DAMMIN. Protein structure modelling was performed with the SAXSTER server on the basis of all available full-length TF structures (i.e. from E. coli, T. maritima and V. cholerae) as templates or RaptorX algorithm based on the EcTF structure. Superposition of […]


Reconstruction of SAXS Profiles from Protein Structures

Comput Struct Biotechnol J
PMCID: 3962079
PMID: 24688746
DOI: 10.5936/csbj.201308006

[…] In 2011, the Zhang lab at the University of Michigan introduced SAXSTER, an online tool to improve protein template recognition by using SAXS profiles[]. In their approach they also simulate the SAXS intensity profile according to the Debye equation. Instead of su […]


Integrative structural modeling with small angle X ray scattering profiles

BMC Struct Biol
PMCID: 3427135
PMID: 22800408
DOI: 10.1186/1472-6807-12-17

[…] ructures cannot be identified using a sequence similarity search. Zheng and Doniach [] used a SAXS profile to filter structures generated by gapless threading on the templates. The recently developed SAXSTER method [] integrates a SAXS-based scoring function with the MUSTER threading algorithm. The SAXS profile fit score is combined with the threading alignment score, resulting in a higher accurac […]


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SAXSTER institution(s)
Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
SAXSTER funding source(s)
This work was supported in part by the National Science Foundation (Career Award 1027394), the National Institute of General Medical Sciences (GM083107 and GM084222), and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq Process 140377/2008-5).

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