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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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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What is Gene Expression?01:42

What is Gene Expression?

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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What is Gene Expression?01:36

What is Gene Expression?

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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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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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Protein Networks02:26

Protein Networks

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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Related Experiment Video

Updated: Feb 24, 2026

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
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GeNET: a web application to explore and share Gene Co-expression Network Analysis data.

Amit P Desai1, Mehdi Razeghin1, Oscar Meruvia-Pastor1,2

  • 1Department of Computer Science, Memorial University of Newfoundland, St. John's, Canada.

Peerj
|August 23, 2017
PubMed
Summary
This summary is machine-generated.

GeNET is a new online tool that helps researchers share and explore gene co-expression network analysis (GCNA) data. It integrates GCNA outputs, enabling easier data sharing and interactive exploration of gene networks.

Keywords:
Data visualizationGeNETGene co-expression network analysis (GCNA)Gene expressionTranscriptomicsWeb tool

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Gene Co-expression Network Analysis (GCNA) is crucial for understanding gene expression profiles.
  • Existing tools for GCNA data visualization have limitations in data integration and online accessibility.
  • Sharing and exploring GCNA data is challenging due to these limitations.

Purpose of the Study:

  • To develop an integrated online platform, GeNET, for sharing and exploring GCNA data.
  • To overcome the limitations of existing tools in handling and presenting GCNA outputs.
  • To facilitate public accessibility and computational analysis of GCNA datasets.

Main Methods:

  • Developed GeNET, a web-based platform for uploading and accessing GCNA data.
  • Implemented functionalities for interactive exploration of genes, gene sets, and modules.
  • Integrated three published GCNA datasets, including one with 17,000 genes and 200 conditions.

Main Results:

  • GeNET provides a user-friendly interface for uploading and sharing GCNA data.
  • The platform enables interactive exploration and visualization of complex gene co-expression networks.
  • Users can download data for further computational analysis, promoting data reuse.

Conclusions:

  • GeNET enhances the accessibility and usability of GCNA data for the research community.
  • The platform facilitates collaboration and discovery by enabling seamless data sharing and exploration.
  • GeNET represents a significant advancement in the field of bioinformatics for gene expression analysis.