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Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

Published on: November 26, 2017

Bioinformatics and proteomics approaches for aging research.

Chaerkady Raghothama¹, H C Harsha, C K Prasad

¹Institute of Bioinformatics, International Tech Park Ltd., 560066, Bangalore, India.

|December 8, 2005

Summary

Aging research faces challenges due to long human lifespans, necessitating studies in model organisms. This study explores genomic, transcriptomic, and proteomic approaches to understand aging mechanisms using bioinformatics and systems biology.

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Area of Science:

Gerontology and Molecular Biology

Background:

Aging is a complex physiological process impacting all organisms.
Human studies are limited by long lifespans, making model organisms crucial for aging research.
Extrapolating findings from model organisms to humans presents challenges due to lifespan differences.

Purpose of the Study:

To discuss advanced genomic, transcriptomic, and proteomic approaches for aging research.
To highlight the utility of bioinformatics and systems biology in dissecting aging mechanisms.
To provide a framework for comprehensive mechanistic insight into the aging process.

Main Methods:

Leveraging large-scale data generation from genomic and proteomic technologies.
Utilizing web-based community resources and databases for data accessibility.
Applying bioinformatics and systems biology methodologies to analyze complex aging data.

Main Results:

Genomic, transcriptomic, and proteomic approaches offer powerful tools for aging research.
Bioinformatics and systems biology provide a framework to analyze large-scale aging data.
These integrated approaches facilitate a deeper mechanistic understanding of aging.

Conclusions:

Advanced molecular technologies and computational approaches are essential for aging research.
Understanding aging requires integrating multi-omics data with systems biology.
This research framework aids in deciphering the complex molecular underpinnings of aging.