Literature DB >> 25873079

Bioinformatics, interaction network analysis, and neural networks to characterize gene expression of radicular cyst and periapical granuloma.

Fabiano de Oliveira Poswar1, Lucyana Conceição Farias2, Carlos Alberto de Carvalho Fraga1, Wilson Bambirra3, Manoel Brito-Júnior1, Manoel Damião Sousa-Neto4, Sérgio Henrique Souza Santos5, Alfredo Maurício Batista de Paula1, Marcos Flávio Silveira Vasconcelos D'Angelo6, André Luiz Sena Guimarães7.   

Abstract

INTRODUCTION: Bioinformatics has emerged as an important tool to analyze the large amount of data generated by research in different diseases. In this study, gene expression for radicular cysts (RCs) and periapical granulomas (PGs) was characterized based on a leader gene approach.
METHODS: A validated bioinformatics algorithm was applied to identify leader genes for RCs and PGs. Genes related to RCs and PGs were first identified in PubMed, GenBank, GeneAtlas, and GeneCards databases. The Web-available STRING software (The European Molecular Biology Laboratory [EMBL], Heidelberg, Baden-Württemberg, Germany) was used in order to build the interaction map among the identified genes by a significance score named weighted number of links. Based on the weighted number of links, genes were clustered using k-means. The genes in the highest cluster were considered leader genes. Multilayer perceptron neural network analysis was used as a complementary supplement for gene classification.
RESULTS: For RCs, the suggested leader genes were TP53 and EP300, whereas PGs were associated with IL2RG, CCL2, CCL4, CCL5, CCR1, CCR3, and CCR5 genes.
CONCLUSIONS: Our data revealed different gene expression for RCs and PGs, suggesting that not only the inflammatory nature but also other biological processes might differentiate RCs and PGs.
Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Endodontics; TH1; TH2; gene; high throughput biology

Mesh:

Year:  2015        PMID: 25873079     DOI: 10.1016/j.joen.2015.02.004

Source DB:  PubMed          Journal:  J Endod        ISSN: 0099-2399            Impact factor:   4.171


  6 in total

1.  Acute oral treatment with resveratrol and Lactococcus Lactis Subsp. Lactis decrease body weight and improve liver proinflammatory markers in C57BL/6 mice.

Authors:  Keila Lopes Mendes; Deborah de Farias Lelis; Daniela Fernanda de Freitas; Luiz Henrique da Silveira; Alfredo Maurício Batista de Paula; André Luiz Sena Guimarães; Janaína Ribeiro Oliveira; Mariléia Chaves Andrade; Sérgio Avelino Mota Nobre; Sérgio Henrique Sousa Santos
Journal:  Mol Biol Rep       Date:  2021-02-14       Impact factor: 2.316

2.  Identification of oral cancer related candidate genes by integrating protein-protein interactions, gene ontology, pathway analysis and immunohistochemistry.

Authors:  Ravindra Kumar; Sabindra K Samal; Samapika Routray; Rupesh Dash; Anshuman Dixit
Journal:  Sci Rep       Date:  2017-05-30       Impact factor: 4.379

3.  Bioinformatics Analysis Reveals Genes Involved in the Pathogenesis of Ameloblastoma and Keratocystic Odontogenic Tumor.

Authors:  Eliane Macedo Sobrinho Santos; Hércules Otacílio Santos; Ivoneth Dos Santos Dias; Sérgio Henrique Santos; Alfredo Maurício Batista de Paula; John David Feltenberger; André Luiz Sena Guimarães; Lucyana Conceição Farias
Journal:  Int J Mol Cell Med       Date:  2016-12-06

4.  Metformin increases PDH and suppresses HIF-1α under hypoxic conditions and induces cell death in oral squamous cell carcinoma.

Authors:  Talita Antunes Guimarães; Lucyana Conceição Farias; Eliane Sobrinho Santos; Carlos Alberto de Carvalho Fraga; Lissur Azevedo Orsini; Leandro de Freitas Teles; John David Feltenberger; Sabrin Ferreira de Jesus; Marcela Gonçalves de Souza; Sérgio Henrique Sousa Santos; Alfredo Maurício Batista de Paula; Ricardo Santiago Gomez; André Luiz Sena Guimarães
Journal:  Oncotarget       Date:  2016-08-23

5.  Apical periodontitis: preliminary assessment of microbiota by 16S rRNA high throughput amplicon target sequencing.

Authors:  Federico Mussano; Ilario Ferrocino; Natalija Gavrilova; Tullio Genova; Alessandro Dell'Acqua; Luca Cocolin; Stefano Carossa
Journal:  BMC Oral Health       Date:  2018-04-02       Impact factor: 2.757

Review 6.  Artificial Intelligence in Dentistry-Narrative Review.

Authors:  Agata Ossowska; Aida Kusiak; Dariusz Świetlik
Journal:  Int J Environ Res Public Health       Date:  2022-03-15       Impact factor: 3.390

  6 in total

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