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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
Mesh Analysis01:20

Mesh Analysis

Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...

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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms.

Saurin D Jani1, Gary L Argraves, Jeremy L Barth

  • 1Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC 29425, USA.

BMC Bioinformatics
|April 3, 2010
PubMed
Summary
This summary is machine-generated.

GeneMesh is a web tool that analyzes DNA microarray data by linking genes to Medical Subject Headings (MeSH) categories. This facilitates exploring gene relationships with biological processes and diseases for hypothesis generation.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • DNA microarray gene expression experiments aim to link differentially expressed genes to biological functions and diseases.
  • Understanding these relationships is crucial for biological discovery.

Purpose of the Study:

  • To introduce GeneMesh, a web-based program for analyzing DNA microarray gene expression data.
  • To facilitate the exploration of relationships between genes and biological concepts.

Main Methods:

  • GeneMesh relates query genes to categories in the Medical Subject Headings (MeSH) hierarchical index.
  • It supports both hypothesis-driven and unbiased relational analyses.
  • The tool integrates with Entrez Gene, Gene Ontology, KEGG pathways, and interaction databases.

Main Results:

  • GeneMesh enables dynamic linking of genes to MeSH categories for analysis.
  • It provides tabular and graphical displays of integrated biological information.
  • Heat maps visualize expression intensity values for gene clusters related to MeSH categories.

Conclusions:

  • GeneMesh is a versatile tool for hypothesis testing and development in gene expression analysis.
  • It enhances biological discovery by linking gene sets to MeSH categories and rich data resources.
  • The tool supports data from various microarray platforms and is freely available online.