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Related Concept Videos

Protein Networks02:26

Protein Networks

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,...
Protein Networks02:26

Protein Networks

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,...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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...
Genomics02:02

Genomics

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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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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Genes2FANs: connecting genes through functional association networks.

Ruth Dannenfelser1, Neil R Clark, Avi Ma'ayan

  • 1Department of Pharmacology and Systems Therapeutics, Systems Biology Center of New York, Mount Sinai School of Medicine, New York, NY 10029, USA.

BMC Bioinformatics
|July 4, 2012
PubMed
Summary

Genes2FANs integrates functional association networks (FANs) with protein-protein interaction (PPI) networks to reveal gene relationships. This approach differentiates disease gene connections, aiding in new biological discoveries and hypothesis generation.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Gene and protein interaction networks are crucial for understanding biological processes.
  • Existing methods often focus on physical or co-expression interactions, potentially missing other functional associations.
  • Functional Association Networks (FANs) incorporate diverse gene properties to identify broader connections.

Purpose of the Study:

  • To develop a tool, Genes2FANs, for building subnetworks that connect gene lists using both FANs and protein-protein interaction (PPI) networks.
  • To provide a web-based platform for exploring gene relationships in human and mouse.
  • To investigate the utility of FANs in understanding disease gene connections.

Main Methods:

  • Genes2FANs utilizes 14 curated FANs and a large-scale PPI network.
  • Input gene lists (human or mouse Entrez gene symbols) are used to generate subnetworks.
  • PubMed search terms can be converted to gene lists via GeneRIF for subnetwork generation.
  • Mouse genes are mapped to human orthologs for integrated analysis.

Main Results:

  • Genes2FANs successfully connects lists of human and mouse genes by building subnetworks.
  • An inverse correlation was observed between PPI-based and FAN-based connections for disease genes.
  • Diseases were categorized based on their predominant connection type (PPI vs. FANs).

Conclusions:

  • Genes2FANs is a valuable tool for interpreting gene/protein list relationships within functional and interaction networks.
  • Combining FANs with PPIs aids in discovering novel biological insights and formulating experimental hypotheses.
  • The distinct connectivity patterns of disease genes (PPI-dominant in cancers, FAN-dominant in others) can inform disease gene discovery strategies.