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

Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Vesicular Tubular Clusters01:45

Vesicular Tubular Clusters

After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
With the help of motor proteins such...
RNA-seq03:21

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...
Chunking01:12

Chunking

Chunking is a powerful cognitive technique that improves short-term memory retention by organizing information into smaller, more manageable units. The brain, limited by working memory capacity, can more easily process and store information when it is divided into "chunks" rather than presented as discrete, unrelated elements. Chunking is especially useful when dealing with large amounts of information, such as numerical sequences, words, or complex ideas.
The principle behind chunking is...
Scatter Plot01:15

Scatter Plot

The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:

You might also read

Related Articles

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

Sort by
Same author

Hospital-initiated community pharmacist medication review post-discharge.

Aging clinical and experimental research·2026
Same author

Unraveling intersectional risks: Postnatal adversities condition the impact of prenatal alcohol exposures on early childhood sleep outcomes.

Development and psychopathology·2026
Same author

Preeclampsia is Associated with Altered Expression of Ferroptosis Biomarkers in Placental but not Maternal Vasculature.

Reproductive sciences (Thousand Oaks, Calif.)·2025
Same author

Re: Enhancing communication equity in critical care: Multimodal and technological approaches to overcome language barriers.

Australian critical care : official journal of the Confederation of Australian Critical Care Nurses·2025
Same author

Sex differences in onset and prevalence of 108 diseases and multimorbidity across lifespan in Yichang, China: quantitative analysis of real-world linked electronic health records.

BMJ open·2025
Same author

Correction: Preadmission medications and recent falls in older inpatients: an observational study.

International journal of clinical pharmacy·2025
Same journal

Tracking Synthetic Adhesins on Bacterial Surfaces with Immunofluorescence Microscopy.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Post-Selection Methods for Analyzing mRNA Display Selections and Optimization of Hits.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

High-Performance Computing in Tandem Mass Spectrometry (MS/MS) Peptide Identification.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Engineering and Adapting Disulfide-Containing Proteins to Enable Intracellular Functionality.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

AI-Driven Protein Research: From Prediction to Design.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for the In Vitro Selection of Protein and Peptide Libraries Using mRNA Display.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: Jul 2, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Clustering.

Geoffrey J McLachlan1, Richard W Bean, Shu-Kay Ng

  • 1ARC Centre of Excellence in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.

Methods in Molecular Biology (Clifton, N.J.)
|August 21, 2008
PubMed
Summary
This summary is machine-generated.

Gene clustering organizes genes with similar behavior across tissues. This study uses model-based clustering with normal mixtures for analyzing tissue samples and gene profiles.

More Related Videos

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

Related Experiment Videos

Last Updated: Jul 2, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Clustering techniques group genes or tissues based on similar behavior across samples.
  • Various methods exist, including hierarchical, k-means, self-organizing maps, and model-based approaches.
  • Gene expression data analysis often relies on these grouping strategies.

Purpose of the Study:

  • To present model-based clustering using normal mixtures.
  • To apply clustering to tissue samples (gene signatures) and gene profiles.
  • To offer a robust method for organizing biological data.

Main Methods:

  • Focuses on mixtures of normals for clustering.
  • Applies clustering to analyze tissue samples and gene expression profiles.
  • Utilizes a model-based approach for data organization.

Main Results:

  • Demonstrates the application of normal mixture models for biological data clustering.
  • Provides a framework for grouping tissue samples based on gene signatures.
  • Enables the organization of gene profiles with similar expression patterns.

Conclusions:

  • Model-based clustering with normal mixtures is effective for gene and tissue analysis.
  • This approach enhances the understanding of gene behavior across different biological samples.
  • Offers a powerful tool for genomic data exploration and interpretation.