Evidence map›Paper›PMID 40808800›Full record

ArticleComputational and structural biotechnology journal2025

Machine learning identification of molecular targets for medulloblastoma subgroups using microarray gene fingerprint analysis.

Alicia Reveles-Espinoza, Ulises Villela, Edgar Hernandez-Martinez, Isaac Chairez, Sergio Juárez-Méndez, J Casanova-Moreno, Ma Del Pilar Eguía-Aguilar, Luis Figueroa-Yáñez, Adriana Vallejo-Cardona, Iván Salgado

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Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Alicia Reveles-EspinozaCentro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Gustavo A. Madero, 07700, Mexico City, Mexico.
Ulises VillelaCentro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Gustavo A. Madero, 07700, Mexico City, Mexico.
Edgar Hernandez-MartinezCentro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Gustavo A. Madero, 07360, Mexico City, Mexico.
Isaac ChairezTecnológio de Monterrey, Campus Guadalajara, Institute of Advanced Materials for Sustainable Manufacturing, Zapopan, 45201, Jalisco, Mexico.
Sergio Juárez-MéndezLaboratorio de Oncología Experimental, Instituto Nacional de Pediatría, Av. Insurgentes Sur 3700 Letra C, Coyoacan, 04530, Mexico City, Mexico.
J Casanova-MorenoCentro de Innovación y Desarrollo Tecnológico en Electroquímica (CIDETEQ), Parque Tecnológico Querétaro, s/n, Pedro Escobedo, 76703, Queretaro, Mexico.
Ma Del Pilar Eguía-AguilarLaboratorio de Investigación en Patología Experimental, Hospital Infantil de México Federico Gómez, 06720, Mexico City, Mexico.
Luis Figueroa-YáñezCentro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Zapopan, 45019, Jalisco, Mexico.
Adriana Vallejo-CardonaCentro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, Guadalajara, 44270, Jalisco, Mexico.
Iván SalgadoCentro de Innovación y Desarrollo Tecnológico en Cómputo, Instituto Politécnico Nacional, Gustavo A. Madero, 07700, Mexico City, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study introduces a structured methodology for the identification of molecular targets that accurately classify medulloblastoma subgroups: WNT, SHH, Group 3 (G3) and Group 4 (G4). An artificial neural network (ANN) model trained on microarray gene expression data determined minimal gene combinations for each subgroup. The classification achieved an average accuracy of 96%, demonstrating the effectiveness of the proposed approach. Feature selection using the Kruskal-Wallis and

Indexed as

Artificial neural networksFeature extractionGene microarrayMedulloblastoma

Identifiers

PMID40808800
PMCPMC12345876

What OpenQuestion holds

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Registered trials

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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.