Analysis of aging-related protein interactome and cross-network module comparisons across tissues provide new insights into aging

Randhawa, Vinay and Kumar, Manoj (2021) Analysis of aging-related protein interactome and cross-network module comparisons across tissues provide new insights into aging. COMPUTATIONAL BIOLOGY AND CHEMISTRY, 92.

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Abstract

Delaying the human aging process and thus eliminating the risk factors for age-related diseases is one of the prime objectives. While various aging-associated genes and proteins have been characterized, which provide a significant understanding of the human aging process, a significant success in regulating aging is not achieved yet. Understanding how aging proteins interact with each other and also with other proteins could provide important insights into the underlying mechanisms governing the aging process. Therefore, in this work, information of gene expression was included to the static aging-related protein interactome to understand the network-based relationships among aging-related essential (AE) proteins, aging-related non-essential (ANE) proteins, and housekeeping-proteins that could regulate or influence aging. Comprehensive analyses provided various systems-level insights into the regulatory characteristics of aging; for example, (i) network-based correlation analysis predicted functional relationships among AE proteins and ANE proteins; (ii) network variability analysis predicted aging to affect different tissues in strikingly different ways by differentially regulating various regulatory interactions; (iii) cross-network comparisons identified two aging-related modules to be significantly conserved across most of the tissues. Overall, the findings obtained during this study could be helpful for researchers to delay, prevent, or even reverse various aspects of the aging.

Item Type: Article
Additional Information: Copyright of this article belongs to ELSEVIER
Uncontrolled Keywords: Aging protein interactome; Cross-network comparison; Network correlation; Network variability.
Subjects: Q Science > QR Microbiology
Depositing User: Dr. K.P.S.Sengar
Date Deposited: 28 Mar 2022 05:28
Last Modified: 28 Mar 2022 05:28
URI: http://crdd.osdd.net/open/id/eprint/2726

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