Methods for Gene Co-expression Network Visualization and Analysis
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2
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bookPart
Data de publicação
2022
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SPRINGER INTERNATIONAL PUBLISHING
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Citação
Moreira-Filho, C. A.; Bando, S. Y.; Bertonha, F. B.; Silva, F. N.; Costa, L. D. F.. Methods for Gene Co-expression Network Visualization and Analysis. In: . Transcriptomics in Health and Disease, Second Edition: SPRINGER INTERNATIONAL PUBLISHING, 2022. p.143-163.
Resumo
Gene network analysis is an important tool for studying the changes in steady states that characterize cell functional properties, the genome-environment interplay, and the health-disease transitions. Moreover, gene co-expression and protein–protein interaction (PPI) data can be integrated with clinical, histopathological, and imaging information – a current practice in systems biology – leading, for instance, to the identification of unique and common drivers for disease conditions. In this chapter the fundamentals for gene co-expression network construction, visualization, and analysis are revised, emphasizing its scale-free nature, the measures that express its most relevant topological features, and methods for network validation. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.
Palavras-chave
Betweenness ity, Disease-related genes, Functional enrichment analysis, Functional genomics, Gene co-expression, Gene network analysis, Gene significance, Genomics, Interactome analysis, Metabolomics, Microarray, Motifs, Network connectivity, Network modules, Network nodes, Network topology, Network validation, Network visualization, Pearson’s correlation coefficient, Protein-protein interaction, Proteomics, RNA-seq, Scale free networks, Scale-free nature, Systems biology, Transcriptional modules, Transcriptomics, Validation
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