About: Self-similarity analysis of eubacteria genome based on weighted graph

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Self-similarity analysis of eubacteria genome based on weighted graph
Creator	Li, Ling Qi, Xiao-Qin Qi, Zhao-Hui Zhang, Zhi-Meng
Source	Elsevier; Medline; PMC
abstract	Abstract We introduce a weighted graph model to investigate the self-similarity characteristics of eubacteria genomes. The regular treating in similarity comparison about genome is to discover the evolution distance among different genomes. Few people focus their attention on the overall statistical characteristics of each gene compared with other genes in the same genome. In our model, each genome is attributed to a weighted graph, whose topology describes the similarity relationship among genes in the same genome. Based on the related weighted graph theory, we extract some quantified statistical variables from the topology, and give the distribution of some variables derived from the largest social structure in the topology. The 23 eubacteria recently studied by Sorimachi and Okayasu are markedly classified into two different groups by their double logarithmic point-plots describing the similarity relationship among genes of the largest social structure in genome. The results show that the proposed model may provide us with some new sights to understand the structures and evolution patterns determined from the complete genomes.
has issue date	2011-07-07(xsd:dateTime)
bibo:doi	10.1016/j.jtbi.2011.03.033
bibo:pmid	21496459
has license	els-covid
sha1sum (hex)	bd4759d35b86cbbbe9d91ee5666334d78fb27afb
schema:url	https://doi.org/10.1016/j.jtbi.2011.03.033
resource representing a document's title	Self-similarity analysis of eubacteria genome based on weighted graph
has PubMed Central identifier	PMC7094106
has PubMed identifier	21496459
schema:publication	Journal of Theoretical Biology
resource representing a document's body	covid:bd4759d35b86cbbbe9d91ee5666334d78fb27afb#body_text
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