@article{MAKHILLJEAS2019141518162,
    title = {Extraction of Essential Genes Based on Network Attributes},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {15},
    pages = {5183-5189},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.5183.5189},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.5183.5189},
    author = {Mohammad-Ashraf,Khalid and},
    keywords = {Genes,genes groups,maximum cliques,genecards,group centrality metrics,network metrics},
    abstract = {Protein and DNA feature’s extraction represents an interesting research subject for a wide range of
relevant applications. In this study, we studied different methods of grouping a large number of genes based
on relations with other genes. We used different network metrics such as centrality degree and betweenness
to find essential genes. We proposed and developed an algorithm to extract the total and weighted strengths
in associating gene’s relations with each other. The results showed that such group related metrics can be used
to effectively extract knowledge about genes and their associations with other genes as well as with diseases.}
    }