title: Bioinformatics, interaction network analysis, and neural networks to characterize gene expression of radicular cyst and periapical granuloma.
abstract: BACKGROUND
  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.
authors: Department of Dentistry, Universidade Estadual de Montes Claros, Minas Gerais, Brazil.
authors: Fabiano de Oliveira
authors: Fde O
authors: Poswar
authors: Department of Physiopathology, Universidade Estadual de Montes Claros, Minas Gerais, Brazil.
authors: Lucyana Conceição
authors: LC
authors: Farias
authors: Department of Dentistry, Universidade Estadual de Montes Claros, Minas Gerais, Brazil.
authors: Carlos Alberto de Carvalho
authors: CA
authors: Fraga
authors: Department of Restorative Dentistry, Faculty of Dentistry, Universidade Federal de Minas Gerais, Minas Gerais, Brazil.
authors: Wilson
authors: W
authors: Bambirra
authors: Department of Dentistry, Universidade Estadual de Montes Claros, Minas Gerais, Brazil.
authors: Manoel
authors: M
authors: Brito-Júnior
authors: Department of Restorative Dentistry, Faculty of Dentistry, Universidade de São Paulo, Ribeirão Preto, São Paulo, Brazil.
authors: Manoel Damião
authors: MD
authors: Sousa-Neto
authors: Department of Physiopathology, Universidade Estadual de Montes Claros, Minas Gerais, Brazil; Department of Computer Science, Universidade Estadual de Montes Claros, Minas Gerais, Brazil;
authors: Sérgio Henrique Souza
authors: SH
authors: Santos
authors: Department of Dentistry, Universidade Estadual de Montes Claros, Minas Gerais, Brazil.
authors: Alfredo Maurício Batista
authors: AM
authors: de Paula
authors: Department of Computer Science, Universidade Estadual de Montes Claros, Minas Gerais, Brazil;
authors: Marcos Flávio Silveira Vasconcelos
authors: MF
authors: D'Angelo
authors: Department of Dentistry, Universidade Estadual de Montes Claros, Minas Gerais, Brazil. Electronic address: andreluizguimaraes@gmail.com.
authors: André Luiz Sena
authors: AL
authors: Guimarães
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D015870:Gene Expression; D053263:Gene Regulatory Networks; D006801:Humans; D016571:Neural Networks, Computer; D010484:Periapical Granuloma / Q000235:genetics*; D011842:Radicular Cyst / Q000235:genetics*
keywords: Endodontics; TH1; TH2; gene; high throughput biology