Back to Journals » Advances and Applications in Bioinformatics and Chemistry » Volume 2

Identification of longevity genes with systems biology approaches

Authors Yuanyou Tan, John M Bush, Weijiu Liu, Fusheng Tang

Published 27 February 2009 Volume 2009:2 Pages 49—56

DOI https://doi.org/10.2147/AABC.S4070

Review by Single-blind

Peer reviewer comments 4

Yuanyou Tan1,3, John M Bush1, Weijiu Liu2, Fusheng Tang1

1Department of Biology, University of Arkansas, Little Rock, AR, USA; 2Department of Mathematics, University of Central Arkansas, Conway, AR, USA; 3Department of Bioengineering, Wuhan University of Science and Engineering, Hubei, China

Abstract: Identification of genes involved in the aging process is critical for understanding the mechanisms of age-dependent diseases such as cancer and diabetes. Measuring the mutant gene lifespan, each missing one gene, is traditionally employed to identify longevity genes. While such screen is impractical for the whole genome due to the time-consuming nature of lifespan assays, it can be achieved by in silico genetic manipulations with systems biology approaches. In this review, we will introduce pilot explorations applying two approaches of systems biology in aging studies. One approach is to predict the role of a specific gene in the aging process by comparing its expression profile and protein–protein interaction pattern with those of known longevity genes (top-down systems biology). The other approach is to construct mathematical models from previous kinetics data and predict how a specific protein contributes to aging and antiaging processes (bottom-up systems biology). These approaches allow researchers to simulate the effect of each gene’s product in aging by in silico genetic manipulations such as deletion or over-expression. Since simulation-based approaches are not as widely used as the other approaches, we will focus our review on this effort in more detail. A combination of hypothesis from data-mining, in silico experimentation from simulations, and wet laboratory validation will make the systematic identification of all longevity genes possible.

Keywords: systems biology, yeast, aging, in silico genetic manipulation, modeling

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF] 

 

Readers of this article also read:

Emerging and future therapies for hemophilia

Carr ME, Tortella BJ

Journal of Blood Medicine 2015, 6:245-255

Published Date: 3 September 2015

Mesenchymal stem cell therapy for osteoarthritis: current perspectives

Wyles CC, Houdek MT, Behfar A, Sierra RJ

Stem Cells and Cloning: Advances and Applications 2015, 8:117-124

Published Date: 28 August 2015

Green synthesis of water-soluble nontoxic polymeric nanocomposites containing silver nanoparticles

Prozorova GF, Pozdnyakov AS, Kuznetsova NP, Korzhova SA, Emel’yanov AI, Ermakova TG, Fadeeva TV, Sosedova LM

International Journal of Nanomedicine 2014, 9:1883-1889

Published Date: 16 April 2014

A novel preparation method for silicone oil nanoemulsions and its application for coating hair with silicone

Hu Z, Liao M, Chen Y, Cai Y, Meng L, Liu Y, Lv N, Liu Z, Yuan W

International Journal of Nanomedicine 2012, 7:5719-5724

Published Date: 12 November 2012

Crystallization after intravitreal ganciclovir injection

Pitipol Choopong, Nattaporn Tesavibul, Nattawut Rodanant

Clinical Ophthalmology 2010, 4:709-711

Published Date: 14 July 2010