Analysis of Nonlinear Gene Expression Progression Reveals Extensive Pathway and Age-Specific Transitions in Aging Human Brains

Open Access

Peer-reviewed

Research Article

Kajia Cao,

Current address: Molecular Genetics Lab, Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America

Affiliations Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Penn Center for Bioinformatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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Paul Ryvkin,

Affiliation Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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Yih-Chii Hwang,

Affiliation Genomics and Computational Biology Graduate Group, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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F. Brad Johnson,

Affiliations Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Institute on Aging, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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Li-San Wang

* E-mail: lswang@mail.med.upenn.edu

Affiliations Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Penn Center for Bioinformatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, Institute on Aging, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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Gene expression
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Aging
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Genetic networks
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Protein interaction networks
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Centrality
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Linear regression analysis
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Biomarkers
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Protein-protein interactions
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