Evidence map›Paper›PMID 42426469›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

RNA-Seq and XAI Can be Used as Tools to Aid Pathologists in the Process of Cancer Diagnosis.

Patricia Porras-Quesada, Pilar Sánchez, Carmen M Morales-Álvarez, Alberto Ramírez-Mena, Maria Jesus Alvarez-Cubero, Luis Javier Martínez-González

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Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

6 authors.

Patricia Porras-QuesadaDepartment of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain.
Pilar SánchezDepartment of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain.
Carmen M Morales-ÁlvarezDepartment of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain.
Alberto Ramírez-MenaIFMIF-DONES Spain Consortium, IFMIF-DONES, Granada, Spain.
Maria Jesus Alvarez-CuberoDepartment of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain.
Luis Javier Martínez-GonzálezDepartment of Biochemistry and Molecular Biology III and Immunology, Faculty of Medicine, University of Granada, Granada, Spain. luisjaviermg@ugr.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA sequencing (RNA-Seq) is an advanced technique that enables the comprehensive analysis of gene expression and the transcriptome in biological samples with exceptional precision and scalability. Leveraging platforms like Illumina, PacBio, and Oxford Nanopore, RNA-Seq has revolutionized cancer research by identifying genes, isoforms, and genetic variants. When combined with bioinformatics tools, it allows the detection of gene expression signatures, alternative splicing events, and profiles of non-coding RNAs. Furthermore, single-cell analysis provides insights into tumor heterogeneity, enhancing diagnostics, prognostics, and the development of personalized therapies.Artificial intelligence (AI), particularly explainable AI (XAI), plays a pivotal role in transcriptomic data analysis. Interpretable models, such as regression analyses or decision trees, and post-hoc techniques like LIME and SHAP, improve the reliability and usability of findings by identifying key genes for clinical decision-making. These tools integrate seamlessly with high-resolution single-cell and three-dimensional analyses, exploring intratumoral heterogeneity and cellular signaling pathways.Addressing the heterogeneity of common cancers demands the integration of sequencing technologies and AI. The combination of short- and long-read RNA-Seq enables the identification of isoforms and splicing events critical to cancer biology. Together, these technologies and approaches optimize diagnostic and therapeutic strategies, paving the way for personalized treatments by detecting and characterizing genetic alterations and their impact on the tumor microenvironment.

Indexed as

Artificial IntelligenceNeoplasmsRNA-SeqSequence Analysis, RNABiomarkers, TumorComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisTranscriptomeBiomarkers, TumorCancer diagnosisExplainable artificial intelligencePersonalized medicineRNA sequencingSingle-cell analysis

Identifiers

PMID42426469

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.