Measuring Inequalities in Gene Co-expression Networks of HIV-1 Infection Using the Lorenz Curve and Gini Coefficient

Chuang, Zhou

doi:10.4172/2153-0602.1000148

J Data Mining Genomics Proteomics

2014

DOI: 10.4172/2153-0602.1000148

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Measuring Inequalities in Gene Co-expression Networks of HIV-1 Infection Using the Lorenz Curve and Gini Coefficient

Zhou Chuang¹

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Bioinformatics Applications in Biological and Clinical Studies

Mao¹,

Hug²

2014

J Data Mining Genomics Proteomics

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Welcome to the first Issue of Volume 5 of the Journal of Data Mining in Genomics and Proteomics (JDMGP). As in previous publications [1,2], articles compiled in the present issue of JDMGP are not centered on a sole topic. Instead, the Publisher, the Editorial Board and Reviewers have succeeded in assembling a compendium of nine articles that cover a wide range of bioinformatics applications ranging from bioinformatics strategies and challenges in proteome analysis to structural biology and the analysis coding or non-coding DNA expression under various conditions to map construction, ranking of genomes and strategies for sequence alignments.

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Bioinformatics Applications in Biological and Clinical Studies

Mao¹,

Hug²

2014

J Data Mining Genomics Proteomics

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Measuring Inequalities in Gene Co-expression Networks of HIV-1 Infection Using the Lorenz Curve and Gini Coefficient

Cited by 1 publication

References 5 publications

Bioinformatics Applications in Biological and Clinical Studies

Bioinformatics Applications in Biological and Clinical Studies

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