Selected article for: "neural network and secondary structure"
Author: Yongjun Tan; Theresa Schneider; Matthew Leong; L Aravind; Dapeng Zhang
Title: Novel Immunoglobulin Domain Proteins Provide Insights into Evolution and Pathogenesis Mechanisms of SARS-Related Coronaviruses
  • Document date: 2020_3_7
    • ID: h5ire02h_7
    Snippet: The secondary structural prediction was conducted using the Jnet (Joint Network) program (27). Jnet is a 110 neural network-based predictor which trains neural networks from three different types of profiles: 111 profile PSSM, profile HMM, and residue frequency profile. It generates a consensus secondary structure 112 with an average accuracy of 72% or greater. 113.....
    Document: The secondary structural prediction was conducted using the Jnet (Joint Network) program (27). Jnet is a 110 neural network-based predictor which trains neural networks from three different types of profiles: 111 profile PSSM, profile HMM, and residue frequency profile. It generates a consensus secondary structure 112 with an average accuracy of 72% or greater. 113

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