Evidence map›Paper›PMID 39695945›Full record

ArticleBMC bioinformatics2024

NERVE 2.0: boosting the new enhanced reverse vaccinology environment via artificial intelligence and a user-friendly web interface.

Andrea Conte, Nicola Gulmini, Francesco Costa, Matteo Cartura, Felix Bröhl, Francesco Patanè, Francesco Filippini

Abstract read
In one paragraph

Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Andrea Conte *Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy.
Nicola Gulmini *Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy.
Francesco Costa *Synthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy.
Matteo CarturaSynthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy.
Felix BröhlBröhl Software Development, Bonn, Germany.
Francesco PatanèSynthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy.
Francesco FilippiniSynthetic Biology and Biotechnology Unit, Department of Biology, University of Padua, Padua, Italy. francesco.filippini@unipd.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVaccines development in this millennium started by the milestone work on Neisseria meningitidis B, reporting the invention of Reverse Vaccinology (RV), which allows to identify vaccine candidates (VCs) by screening bacterial pathogens genome or proteome through computational analyses. When NERVE (New Enhanced RV Environment), the first RV software integrating tools to perform the selection of VCs, was released, it prompted further development in the field. However, the problem-solving potential of most, if not all, RV programs is still largely unexploited by experimental vaccinologists that impaired by somehow difficult interfaces, requiring bioinformatic skills.

resultsWe report here on the development and release of NERVE 2.0 (available at: https://nerve-bio.org ) which keeps the original integrative and modular approach of NERVE, while showing higher predictive performance than its previous version and other web-RV programs (Vaxign and Vaxijen). We renewed some of its modules and added innovative ones, such as Loop-Razor, to recover fragments of promising vaccine candidates or Epitope Prediction for the epitope prediction binding affinities and population coverage. Along with two newly built AI (Artificial Intelligence)-based models: ESPAAN and Virulent. To improve user-friendliness, NERVE was shifted to a tutored, web-based interface, with a noSQL-database to consent the user to submit, obtain and retrieve analysis results at any moment.

conclusionsWith its redesigned and updated environment, NERVE 2.0 allows customisable and refinable bacterial protein vaccine analyses to all different kinds of users.

Indexed as

Artificial IntelligenceSoftwareComputational BiologyEpitopesHumansInternetUser-Computer InterfaceVaccinologyEpitopesArtificial intelligenceMachine learningModular softwareReverse vaccinologyUser-friendly websiteVaccine candidates

Identifiers

PMID39695945
PMCPMC11654298

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.