Evidence map›Paper›PMID 39312174›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

MolPredictX: A Pioneer Mobile App Version for Online Biological Activity Predictions by Machine Learning Models.

Marcus Tullius Scotti, Emmanuella Faustino Albuquerque, Ciro Gomes da Silva Junior, Renata P B Menezes, Chonny Herrera-Acevedo, Natália F Sousa, Lucas Ferreira Calado, Eduardo Henrique Pessoa Alves, Luciana Scotti

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Exploring Nepicastat Activity: Beyond DβH.International journal of molecular sciences · 2025
    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

9 authors.

Marcus Tullius ScottiPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Emmanuella Faustino AlbuquerquePost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Ciro Gomes da Silva JuniorPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Renata P B MenezesPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Chonny Herrera-AcevedoPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Natália F SousaPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Lucas Ferreira CaladoPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Eduardo Henrique Pessoa AlvesPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.
Luciana ScottiPost-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraíba, João Pessoa, PB, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MolPredictX is a free-access web tool in which it is possible to analyze the prediction of biological activity of chemical molecules. MolPredictX has been available online to the general public for just over a year and has now gone through its first update. We also developed its version for android, being the first free app capable of predicting biological activities. MolPredictX is available for free at https://www.molpredictX.ufpb.br/ , and its mobile application version can be obtained from Google Play.

Indexed as

Machine LearningMobile ApplicationsSoftwareComputational BiologyHumansInternetComputer-aided drug designQuantitative structure activity relationships

Identifiers

PMID39312174

What OpenQuestion holds

Textmetadata
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.