COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning

Article activity feed

1. Version published to 10.3389/fimmu.2020.01581

   Jul 3, 2020
2. 

   ScreenIT

   Jun 5, 2020

   SciScore for 10.1101/2020.03.20.000141: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   Annotation of literature and database records: We annotated peer-reviewed journal articles stored in the PubMed database and the ClinicalTrials.gov database.	PubMed suggested: (PubMed, RRID:SCR_004846)
   Specifically, the positive samples in the training data included 397 bacterial and 178 viral protective antigens (PAgs) recorded in the Protegen database30 after removing homologous proteins with over 30% sequence identity.	Protegen suggested: None
   The linear B cell epitopes were predicted using the BepiPred 2.0 with a cutoff of 0.55 score68.	BepiPred suggested: (BepiPred-2.0, RRID:SCR_018499)

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   Result…

   SciScore for 10.1101/2020.03.20.000141: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   Annotation of literature and database records: We annotated peer-reviewed journal articles stored in the PubMed database and the ClinicalTrials.gov database.	PubMed suggested: (PubMed, RRID:SCR_004846)
   Specifically, the positive samples in the training data included 397 bacterial and 178 viral protective antigens (PAgs) recorded in the Protegen database30 after removing homologous proteins with over 30% sequence identity.	Protegen suggested: None
   The linear B cell epitopes were predicted using the BepiPred 2.0 with a cutoff of 0.55 score68.	BepiPred suggested: (BepiPred-2.0, RRID:SCR_018499)

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   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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   Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

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   Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
   

   Identifier	Status	Title
   NCT04283461	Active, not recruiting	Safety and Immunogenicity Study of 2019-nCoV Vaccine (mRNA-1…

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   Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   Results from rtransparent:

   • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
   • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
   • No protocol registration statement was detected.

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   Read the original source
3. 

   Version published to 10.1101/2020.03.20.000141v2 on bioRxiv

   Mar 23, 2020
4. 

   Version published to 10.1101/2020.03.20.000141v1 on bioRxiv

   Mar 21, 2020