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DNA Microarrays

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...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Related Experiment Video

Updated: Apr 28, 2026

High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

Published on: August 12, 2019

Using semantic web technologies to annotate and align microarray designs.

Sebastian Szpakowski¹, James McCusker², Michael Krauthammer²

¹Program for Computational Biology and Bioinformatics (CBB), Yale University School of Medicine, New Haven, CT. ; Department of Pathology, Yale University School of Medicine, New Haven, CT.

Cancer Informatics

|June 7, 2014

Summary

This summary is machine-generated.

This study introduces the Genomic Element Ontology (GELO) to align gene expression microarray data. GELO facilitates integrating diverse omics data, particularly for cancer research, by linking probes to genomic elements.

Keywords:

annotation data integration genomics ontology semantic web

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Last Updated: Apr 28, 2026

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Published on: October 28, 2011

Area of Science:

Bioinformatics
Genomics
Ontology Engineering

Background:

Gene expression microarray data analysis requires robust methods for data integration.
Existing ontologies may not fully capture the genomic context of microarray probes.
Semantic web technologies offer potential for enhanced data representation and querying.

Purpose of the Study:

To annotate and align gene expression microarray designs using a novel ontology, GELO.
To leverage GELO and Sequence Ontology (SO) for semantic representation of genomically-aligned data.
To demonstrate the utility of GELO for assessing array design coverage and overlap.

Main Methods:

Mapping array probes to genomic coordinates.
Utilizing Sequence Ontology (SO) for representing genomic elements (genes, transcripts, miRNA).
Employing SPARQL to create explicit links between probes and genomic elements within a semantic web environment.

Main Results:

Successful annotation and alignment of two gene expression microarray designs using GELO.
Demonstrated ability to determine element coverage and genomic overlap between array designs.
Established explicit semantic links between probes and genomic elements.

Conclusions:

GELO provides a framework for semantic integration of gene expression data.
The approach enhances the analysis of genomic element coverage and overlap for microarray designs.
This method holds promise for integrating cancer data across multiple omics studies.