Selected article for: "bioinformatic tool and human population"
Author: Beltrán Lissabet, Jorge Félix; Belén, Lisandra Herrera; Farias, Jorge G.
Title: AntiVPP 1.0: A portable tool for prediction of antiviral peptides
  • Cord-id: k935v0z9
  • Document date: 2019_2_19
    • ID: k935v0z9
    Snippet: Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity and constitute excellent alternatives for the treatment of viral infections. In the present study, we developed AntiVPP 1.0, an accurate bioinformatic tool that uses the Random Forest algorithm for antiviral peptide predictions. The model of AntiVPP 1
    Document: Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity and constitute excellent alternatives for the treatment of viral infections. In the present study, we developed AntiVPP 1.0, an accurate bioinformatic tool that uses the Random Forest algorithm for antiviral peptide predictions. The model of AntiVPP 1.0 for antiviral peptide predictions uses several features of 1088 peptides for training and validation. During the validation of the model we achieved the TPR = 0.87, SPC = 0.97, ACC = 0.93 and MCC = 0.87 performance measures, which were indicative of a robust model. AntiVPP 1.0 is a fast, accurate and intuitive software focused on the assessment of antiviral peptides candidates. AntiVPP 1.0 is available at https://github.com/bio-coding/AntiVPP.

    Search related documents:
    Co phrase search for related documents
    • accuracy acc specificity and machine learning: 1, 2, 3
    • accuracy score function and machine learning: 1
    • activity show and machine learning: 1, 2, 3, 4, 5, 6