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Extracting Information from Gene Coexpression Networks of Rhizobium leguminosarum .

Javier Pardo-DiazMariano Beguerisse-DíazPhilip S PooleCharlotte M DeaneGesine Reinert
Published in: Journal of computational biology : a journal of computational molecular cell biology (2022)
Nitrogen uptake in legumes is facilitated by bacteria such as Rhizobium leguminosarum . For this bacterium, gene expression data are available, but functional gene annotation is less well developed than for other model organisms. More annotations could lead to a better understanding of the pathways for growth, plant colonization, and nitrogen fixation in R. leguminosarum . In this study, we present a pipeline that combines novel scores from gene coexpression network analysis in a principled way to identify the genes that are associated with certain growth conditions or highly coexpressed with a predefined set of genes of interest. This association may lead to putative functional annotation or to a prioritized list of genes for further study.
Keyphrases
  • genome wide
  • network analysis
  • genome wide identification
  • gene expression
  • dna methylation
  • copy number
  • genome wide analysis
  • transcription factor
  • healthcare
  • rna seq
  • single cell
  • big data
  • gram negative
  • cell wall