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DExplore: An Online Tool for Detecting Differentially Expressed Genes from mRNA Microarray Experiments.
Katsiki, Anna D; Karatzas, Pantelis E; De Lastic, Hector-Xavier; Georgakilas, Alexandros G; Tsitsilonis, Ourania; Vorgias, Constantinos E.
Afiliação
  • Katsiki AD; Department of Biology, School of Science, National and Kapodistrian University of Athens, 15784 Athens, Greece.
  • Karatzas PE; Unit of Process Control and Informatics, Department of Process Analysis and Plant Design, School of Chemical Engineering, National Technical University of Athens (NTUA), Zografou Campus, 15780 Athens, Greece.
  • De Lastic HX; DNA Damage Laboratory, Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), Zografou Campus, 15780 Athens, Greece.
  • Georgakilas AG; DNA Damage Laboratory, Physics Department, School of Applied Mathematical and Physical Sciences, National Technical University of Athens (NTUA), Zografou Campus, 15780 Athens, Greece.
  • Tsitsilonis O; Department of Biology, School of Science, National and Kapodistrian University of Athens, 15784 Athens, Greece.
  • Vorgias CE; Department of Biology, School of Science, National and Kapodistrian University of Athens, 15784 Athens, Greece.
Biology (Basel) ; 13(5)2024 May 16.
Article em En | MEDLINE | ID: mdl-38785833
ABSTRACT
Microarray experiments, a mainstay in gene expression analysis for nearly two decades, pose challenges due to their complexity. To address this, we introduce DExplore, a user-friendly web application enabling researchers to detect differentially expressed genes using data from NCBI's GEO. Developed with R, Shiny, and Bioconductor, DExplore integrates WebGestalt for functional enrichment analysis. It also provides visualization plots for enhanced result interpretation. With a Docker image for local execution, DExplore accommodates unpublished data. To illustrate its utility, we showcase two case studies on cancer cells treated with chemotherapeutic drugs. DExplore streamlines microarray data analysis, empowering molecular biologists to focus on genes of biological significance.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Biology (Basel) Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Biology (Basel) Ano de publicação: 2024 Tipo de documento: Article