Selected article for: "minimum free energy and predict structure"

Author: Delli Ponti, Riccardo; Marti, Stefanie; Armaos, Alexandros; Tartaglia, Gian Gaetano
Title: A high-throughput approach to profile RNA structure
  • Document date: 2017_3_17
  • ID: k23xlzj0_19
    Snippet: We used RNAstructure with the Fold module and the minimum free energy flag to predict the best RNA secondary structure of each RNA sequence (17, 18) . To mimic experimental constraints in the RNAstructure algorithm, CROSS Global scores were normalized to lie in the range of SHAPE reactivities: first the scores were multiplied by −1, then linearly mapped to [0,1]. Scores >0.65 were then assigned a SHAPE reactivity of 1; scores <0.35 were assigne.....
    Document: We used RNAstructure with the Fold module and the minimum free energy flag to predict the best RNA secondary structure of each RNA sequence (17, 18) . To mimic experimental constraints in the RNAstructure algorithm, CROSS Global scores were normalized to lie in the range of SHAPE reactivities: first the scores were multiplied by −1, then linearly mapped to [0,1]. Scores >0.65 were then assigned a SHAPE reactivity of 1; scores <0.35 were assigned a reactivity of 0; scores >0.35 and <0.65 were linearly mapped to (0,1). We used the Partition and Probability Plot (with -text flag) modules of RNAstructure to compute the AUC based on the probabilities (17, 18) . We employed the package Scorer to calculate the positive predictive values (PPVs) and true positive rates (TPRs) for the specific structures.

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