A genetic algorithm for iterative fitting of SAXS data is presented. The algorithm described produces fast convergence to a fittest model mass distribution compatible with experimental data. This method affords a dramatic reduction of processor time required by other SAXS fitting methods and can be applied to any kind of structure, the only requirement is the target profile. The effectiveness of the procedure is demonstrated with synthetic objects and by deriving the low resolution model of a known protein structure from their corresponding computed SAXS profile.
J M ANDREU ,F MORAN ,J F DIAZ ,E PANTOS ,P CHACON ,
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