Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Cholinergic nucleus degeneration and its association with gait impairment in Parkinson's disease.

Journal of neuroengineering and rehabilitation·2024

Same author

Association between maternal lipid profiles and vitamin D status in second trimester and risk of LGA or SGA: a retrospective study.

Frontiers in endocrinology·2024

Same author

A preliminary probabilistic nomogram model for predicting renal arteriolar damage in IgA nephropathy from clinical parameters.

Frontiers in immunology·2024

Same author

Nitrous oxide abuse in a 21-year-old female: a case report and review of literature.

Frontiers in neurology·2024

Same author

Methionine Source and Level Modulate Gut pH, Amino Acid Transporters and Metabolism Related Genes in Broiler Chickens.

Journal of agricultural and food chemistry·2024

Same author

EQ-5D-5L Population Scores in Mainland China: Results From a Nationally Representative Survey 2021.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2024

Search research articles

Related Experiment Video

Updated: Jun 22, 2026

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Published on: October 4, 2019

Microarray gene cluster identification and annotation through cluster ensemble and EM-based informative textual

Xiaohua Hu¹, E K Park, Xiaodan Zhang

¹Henan University, Kaifeng 475001, China. thu@cis.drexel.edu

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society

|June 17, 2009

Summary

This study introduces Gene Expression Miner, a unified system for gene expression analysis. It integrates cluster ensemble and text summarization to generate high-quality gene clusters and identify their biological mechanisms.

More Related Videos

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Related Experiment Videos

Last Updated: Jun 22, 2026

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy

Published on: October 4, 2019

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Clustering gene expression data is crucial for identifying biological mechanisms.
Current methods struggle with unknown data distributions and selecting appropriate clustering algorithms.
Interpreting gene clusters and assessing clustering quality are often treated as separate problems.

Purpose of the Study:

To develop a unified system, Gene Expression Miner, for comprehensive gene expression data analysis.
To address challenges in generating high-quality gene clusters and identifying their biological mechanisms.
To integrate cluster ensemble, text clustering, and multidocument summarization.

Main Methods:

Developed a novel cluster ensemble approach for high-quality gene cluster generation.
Implemented an expectation-maximization based algorithm for text summarization within gene clusters.
Combined extracted topical terms to form biological explanations for gene clusters.

Main Results:

The Gene Expression Miner system successfully generates high-quality gene clusters.
The system provides informative key terms that explain the biological significance of each gene cluster.
Experimental results validate the effectiveness of the integrated approach.

Conclusions:

Gene Expression Miner offers a principled and general approach to gene expression analysis.
The unified system effectively addresses the separate challenges of clustering quality and cluster interpretation.
This integrated system enhances the ability to discover biological mechanisms from gene expression data.