ShaKer

ShaKer is a software tool that predicts SHAPE reactivity data for RNA molecules using a machine-learning approach based on graph kernels. Unlike other methods that require a manually curated reference structure, ShaKer predicts reactivity data solely based on the RNA sequence by sampling the ensemble of possible structures, makes ShaKer well-suited for experiment-driven, transcriptome-wide SHAPE data prediction, which can aid in studying RNA structuredness and improving predictions of RNA structure and RNA-RNA interactions.

Topic

RNA;Structure prediction;Machine learning

Detail

  • Operation: RNA secondary structure prediction;RNA structure prediction;Protein secondary structure prediction

  • Software interface: -

  • Language: Python

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: German Research Foundation (DFG) and Germany’s Excellence Strategy.

  • Input: -

  • Output: -

  • Contact: Rolf Backofen backofen@informatik.uni-freiburg.de

  • Collection: -

  • Maturity: -

Publications

Download and documentation

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