Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

What is Gene Expression?01:42

What is Gene Expression?

196.6K
Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
196.6K
What is Gene Expression?01:36

What is Gene Expression?

11.4K
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
11.4K
RNA-seq03:21

RNA-seq

12.0K
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...
12.0K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

16.5K
Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
16.5K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

5.6K
5.6K
Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

24.8K
Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...
24.8K

You might also read

Related Articles

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

Sort by
Same author

Comparative NMR-Based Metabolomic and Functional Assessment of Fruit and Vegetable Extracts under Regenerative Agricultural Practices.

Journal of agricultural and food chemistry·2026
Same author

Decoding the reproductive microbiome: enabling clinical and biological insights through machine and deep learning.

Frontiers in endocrinology·2026
Same author

MRI-based assessment and surveillance in watch-and-wait for rectal cancer: a multidisciplinary review.

European journal of radiology·2026
Same author

Solubility-improved and antitumor activity of (-)-cannabidiol conjugates.

Journal of cannabis research·2026
Same author

Salt exposure disrupts memory retrieval in habituation and conditioned place preference in planaria (Dugesia japonica).

Journal of comparative psychology (Washington, D.C. : 1983)·2026
Same author

Automated Lesion Segmentation in Medical Imaging via Integration of nnU-Net Optimization and SAM Approach.

Biomedical engineering and computational biology·2026
Same journal

Epidemiological characteristics of amebiasis in Japan from 2001 to 2022.

PloS one·2026
Same journal

Longitudinal associations of academic stress with eating related patterns, nutrition, somatic indicators, and depressive symptoms in university students: A study protocol.

PloS one·2026
Same journal

Pollution removal efficiency enhancement by agricultural biomass additions in constructed wetlands: A framework integrating meta-analysis with explainable machine learning.

PloS one·2026
Same journal

Insulation failure mapping on power transformer bushing using FRA and electrostatic simulation.

PloS one·2026
Same journal

Enhancing medical Q&A systems with multimodal knowledge graphs and dual-layer attention mechanisms.

PloS one·2026
Same journal

UAMP: Consistent video object segmentation with uncertainty-aware memory propagation.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Jan 29, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

383

Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene

Daniel Castillo1, Juan Manuel Galvez1, Luis J Herrera1

  • 1Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain.

Plos One
|February 13, 2019
PubMed
Summary
This summary is machine-generated.

This study integrates gene expression data from Microarray and RNA-seq platforms to identify key genes distinguishing leukemia types. A novel

More Related Videos

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
06:24

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

4.1K
Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
13:14

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

12.2K

Related Experiment Videos

Last Updated: Jan 29, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
05:07

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

Published on: November 7, 2025

383
Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
06:24

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

4.1K
Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
13:14

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

12.2K

Area of Science:

  • Bioinformatics
  • Genomics
  • Machine Learning

Background:

  • Massive sequencing data and advancements in machine learning enable efficient biological data analysis.
  • Biological disease information is often fragmented across diverse experiments and technologies, necessitating data integration.
  • Integrating data from Microarray and RNA-seq platforms is crucial for comprehensive disease analysis.

Purpose of the Study:

  • To integrate data from multiple Microarray and RNA-seq platforms for a multiclass leukemia study.
  • To introduce and evaluate a novel 'coverage' parameter for identifying differentially expressed genes with high discernment capability.
  • To select and validate a minimal set of genes capable of distinguishing between four main types of leukemia.

Main Methods:

  • Integration of Microarray and RNA-seq data for gene expression quantification across four leukemia types.
  • Development and application of a 'coverage' parameter to assess gene discernment capability.
  • Utilized ANOVA statistical tests for parameter evaluation and gene filtering.
  • Employed Minimum-Redundancy Maximum-Relevance (mRMR) for gene selection and ordering.
  • Applied four classification techniques to assess the performance of selected genes.

Main Results:

  • Successfully integrated data from diverse sequencing platforms for a multiclass leukemia gene expression study.
  • The novel 'coverage' parameter demonstrated significant filtering power, validated by ANOVA.
  • Identified 42 highly relevant expressed genes, with the top 10 showing outstanding classification performance.
  • Literature review confirmed the biological relevance of the selected genes to leukemia.

Conclusions:

  • The study successfully integrated multi-platform gene expression data for leukemia classification.
  • The novel 'coverage' parameter is effective in identifying genes crucial for discerning multiple leukemia types.
  • A small subset of highly relevant genes can accurately distinguish between different leukemia subtypes, paving the way for improved diagnostics.