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• W2893745739 abstract "Abstract Motivation Computational protein design (CPD) calculations rely on the generation of large amounts of data on the search for the best sequences. As such, CPD workflows generally include the batch generation of designed decoys (sampling) followed by ranking and filtering stages to select those with optimal metrics (scoring). Due to these factors, the proper analysis of the decoy population is a key element for the effective selection of designs for experimental validation. Results Here, we present a set of tools for the analysis of protein design ensembles. The tool is oriented towards protein designers with basic coding training aiming to process efficiently their decoy sets as well as for protocol developers interested in benchmarking their new approaches. Although initially devised to process Rosetta design outputs, the library is extendable to other design tools. Availability and Implementation rstoolbox is implemented for python2.7 and 3.5+. Code is freely available at https://github.com/lpdi-epfl/rstoolbox under the MIT license. Full documentation and examples can be found at https://lpdi-epfl.github.io/rstoolbox ." @default.
• W2893745739 created "2018-10-05" @default.
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• W2893745739 date "2018-09-27" @default.
• W2893745739 modified "2023-10-18" @default.
• W2893745739 title "rstoolbox: management and analysis of computationally designed structural ensembles" @default.
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• W2893745739 doi "https://doi.org/10.1101/428045" @default.
• W2893745739 hasPublicationYear "2018" @default.
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