Evidence map›Paper›PMID 35047951›Full record

ArticleFrontiers in medical technology2021

ViralFP: A Web Application of Viral Fusion Proteins.

Pedro Moreira, Ana Marta Sequeira, Sara Pereira, Rúben Rodrigues, Miguel Rocha, Diana Lousa

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medical technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 47% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Machine and deep learning to predict viral fusion peptides.Computational and structural biotechnology journal · 2025
    Article
  2. Review
  3. ViralFP: A Web Application of Viral Fusion Proteins.Frontiers in medical technology · 2021
    Article
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

6 authors at 2 institutions in 1 country.

Pedro MoreiraCentro de Engenharia Biológica, Escola de Engenharia da Universidade do Minho, Braga, Portugal.
Ana Marta SequeiraCentro de Engenharia Biológica, Escola de Engenharia da Universidade do Minho, Braga, Portugal.
Sara PereiraITQB NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal.
Rúben RodriguesCentro de Engenharia Biológica, Escola de Engenharia da Universidade do Minho, Braga, Portugal.
Miguel RochaCentro de Engenharia Biológica, Escola de Engenharia da Universidade do Minho, Braga, Portugal.
Diana LousaITQB NOVA, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal.
University of Minho · PTUniversidade Nova de Lisboa · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral fusion proteins are attached to the membrane of enveloped viruses (a group that includes Coronaviruses, Dengue, HIV and Influenza) and catalyze fusion between the viral and host membranes, enabling the virus to insert its genetic material into the host cell. Given the importance of these biomolecules, this work presents a centralized database containing the most relevant information on viral fusion proteins, available through a free-to-use web server accessible through the URL https://viralfp.bio.di.uminho.pt/. This web application contains several bioinformatic tools, such as Clustal sequence alignment and Weblogo, including as well a machine learning-based tool capable of predicting the location of fusion peptides (the component of fusion proteins that inserts into the host's cell membrane) within the fusion protein sequence. Given the crucial role of these proteins in viral infection, their importance as natural targets of our immune system and their potential as therapeutic targets, this web application aims to foster our ability to fight pathogenic viruses.

Indexed as

databasefusion peptidesfusion proteinsmachine learningweb application

Identifiers

PMID35047951
PMCPMC8757699
OpenAlexW3194095911

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.