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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...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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...

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Related Experiment Video

Updated: May 23, 2026

Pattern-based Search of Epigenomic Data Using GeNemo
06:38

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

ArraySearch: A Web-Based Genomic Search Engine.

Tyler J Wilson1, Steven X Ge

  • 1Department of Mathematics and Statistics, South Dakota State University, P.O. Box 2220, Brookings, SD 57007, USA.

Comparative and Functional Genomics
|April 5, 2012
PubMed
Summary
This summary is machine-generated.

ArraySearch analyzes gene expression data by finding statistical correlations with public archives. This tool helps researchers interpret new genomics data by comparing it to existing expression signatures.

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Last Updated: May 23, 2026

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Microarray technology generates vast amounts of genomics data.
  • Accumulated genomics data can serve as a valuable knowledge base for interpreting new experimental findings.
  • Existing public gene expression data requires effective tools for analysis and comparison.

Purpose of the Study:

  • To introduce ArraySearch, a novel tool for analyzing gene expression data.
  • To enable researchers to statistically correlate new gene expression profiles with public expression signatures.
  • To provide a method for exploring and interpreting experimental data using a large public archive.

Main Methods:

  • ArraySearch identifies statistical correlations between query gene expression profiles and public expression signatures.
  • Searches can be initiated with a list of genes to find relevant experiments.
  • Alternatively, searches can be performed using gene expression signatures from new experiments.

Main Results:

  • The system returns experiments where queried genes are collectively significantly up- or downregulated.
  • It facilitates the comparison of new experimental data against a comprehensive public archive of expression signatures.
  • Provides a statistical approach for biological researchers to interpret their own gene expression data.

Conclusions:

  • ArraySearch empowers biological researchers by offering a statistical method for data exploration.
  • It leverages public genomics data to aid in the interpretation of novel experimental results.
  • The tool enhances the utility of accumulated gene expression data as a research knowledge base.