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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Handling High-Throughput Omics Data for Systems Genetics Analysis.

Francesco Pesce1, Paolo Protopapa2

  • 1Department of Emergency and Organ Transplantation, Nephrology, Dialysis and Transplantation Unit, University of Bari "A. Moro", Bari, Italy. f.pesce81@gmail.com.

Methods in Molecular Biology (Clifton, N.J.)
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PubMed
Summary

Integrating multiple omics data types, like genomics and transcriptomics, offers deeper insights into complex diseases than single omics alone. Systems Genetics enables pinpointing genetic variants linked to gene co-expression networks for pathway analysis.

Keywords:
BioinformaticsBiostatisticsGene expressionOmicsSystems BiologySystems Genetics

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Area of Science:

  • Biomedical Informatics
  • Systems Biology
  • Genetics

Background:

  • Omics data (genomics, transcriptomics, proteomics, metabolomics) are increasingly abundant, aiding disease mechanism discovery.
  • Single omics analyses have limitations in fully dissecting complex biological systems.
  • Integrating diverse omics data is crucial for a comprehensive understanding of disease pathophysiology.

Purpose of the Study:

  • To present a versatile bioinformatic protocol for Systems Genetics analysis.
  • To identify master regulator genes influencing biological pathways in specific cellular conditions.
  • To leverage integrated omics data for deeper biological insights.

Main Methods:

  • Development of a bioinformatic protocol for Systems Genetics.
  • Integration of genetics and gene expression data.
  • Analysis of Cytotoxic T Lymphocytes (CTLs) data.

Main Results:

  • The protocol facilitates the integration of genetic variants with gene co-expression networks.
  • It enables the identification of key genes (master regulators) impacting cellular pathways.
  • Demonstrates a strategy to overcome single-omics limitations.

Conclusions:

  • Systems Genetics offers a powerful approach to analyze complex biological data.
  • The presented protocol provides a versatile tool for investigating cellular states and pathways.
  • Integrated omics analysis is essential for advancing our understanding of disease and identifying therapeutic targets.