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

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...
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an organic...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

You might also read

Related Articles

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

Sort by
Same author

Serum microRNA Profiles Reflect Differentiation Status and Age in Early Gastric Cancer.

Biomolecules·2026
Same author

Electron-Induced C─F Bond Activation in Sn<sub>6</sub>-oxo Cluster Resist for Enhanced Sensitivity and Sub-10-nm Patterning.

Angewandte Chemie (International ed. in English)·2026
Same author

2D Ultrasound Elasticity Imaging of Abdominal Aortic Aneurysms Using Deep Neural Networks.

IEEE transactions on computational imaging·2026
Same author

Toward Patient-Specific Partial Point Cloud to Surface Completion for Pre to Intra-operative Registration in Image-Guided Liver Interventions.

Medical Image Understanding and Analysis. Medical Image Understanding and Analysis (Conference)·2026
Same author

Evaluation of Intra-operative Patient-specific Methods for Point Cloud Completion for Minimally Invasive Liver Interventions.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

Investigating the Domain Adaptability of General-Purpose Foundation Models for Left Atrium Segmentation from MR Images.

Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference)·2026

Related Experiment Video

Updated: Jun 26, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Non-negative matrix factorization of gene expression profiles: a plug-in for BRB-ArrayTools.

Qihao Qi1, Yingdong Zhao, MingChung Li

  • 1Department of Biochemistry and Molecular Biology, Georgetown University School of Medicine, 3900 Reservoir Rd. NW, Washington, DC 20057-1455, USA.

Bioinformatics (Oxford, England)
|January 10, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a Non-negative matrix factorization (NMF) plug-in for BRB-ArrayTools, enabling unsupervised sample clustering in gene expression data. The tool also features Semi-NMF for handling diverse data types and provides comparative analysis with K-means clustering.

More Related Videos

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets
03:37

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

Published on: March 1, 2024

Related Experiment Videos

Last Updated: Jun 26, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
08:00

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets
03:37

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

Published on: March 1, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Non-negative matrix factorization (NMF) is a powerful algorithm for analyzing high-dimensional data.
  • BRB-ArrayTools is a widely adopted software for gene expression analysis with a large global user base.

Purpose of the Study:

  • To develop and integrate an NMF analysis plug-in into BRB-ArrayTools.
  • To enable unsupervised sample clustering for microarray gene expression data.
  • To incorporate Semi-NMF for handling log-ratio data with positive and negative elements.

Main Methods:

  • Development of an NMF plug-in for BRB-ArrayTools.
  • Implementation of Semi-NMF algorithm for enhanced data handling.
  • Generation of heat maps for sample clusters and differentially expressed genes.
  • Comparative analysis with K-means clustering results.

Main Results:

  • Successful integration of NMF and Semi-NMF algorithms into BRB-ArrayTools.
  • Visualization of sample clusters and differentially expressed genes through heat maps.
  • Provision of biological annotations for identified clusters and genes.
  • Direct comparison of NMF/Semi-NMF clustering with K-means.

Conclusions:

  • The developed NMF plug-in enhances BRB-ArrayTools capabilities for gene expression data analysis.
  • The tool facilitates unsupervised sample clustering and identification of biologically relevant patterns.
  • The inclusion of Semi-NMF expands the applicability to a wider range of data types.
  • The plug-in offers a valuable resource for researchers in genomics and bioinformatics.