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

¹H NMR Signal Multiplicity: Splitting Patterns01:13

¹H NMR Signal Multiplicity: Splitting Patterns

6.9K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
6.9K
Genomics02:02

Genomics

40.8K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
40.8K
The Extracellular Matrix01:42

The Extracellular Matrix

89.3K
Overview
89.3K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

758
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
758
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.6K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.1K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Pipa Qingfei Yin Ameliorates Acne Inflammation in Mice via Suppressing Neutrophil Extracellular Traps.

Microbiology and immunology·2026
Same author

Collaborative improvement effect of xanthan gum and L-arginine on myofibrillar protein-based emulsion under low sodium and low oil phase: Interfacial behavior, rheology and 3D printability.

Food chemistry·2026
Same author

Hippocampal neuronal hypoexcitability contributes to PTSD-like phenotypes in the experimental autoimmune encephalomyelitis model.

Frontiers in psychiatry·2026
Same author

Exosome-derived LncRNAs in bone remodeling: recent advances and future directions for bone disease therapy.

Stem cell research & therapy·2026
Same author

Help-Seeking Behavior of Adults with Adverse Childhood Experiences in Rural China.

Behavioral sciences (Basel, Switzerland)·2026
Same author

Prediction Error in Quality-Adjusted Life Years in Economic Evaluations of Immune Checkpoint Inhibitors: A Comparison Based on Projected and Observed Updated Survival.

PharmacoEconomics - open·2026

Related Experiment Video

Updated: Feb 8, 2026

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow
12:53

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow

Published on: June 14, 2017

11.2K

Matrix Integrative Analysis (MIA) of Multiple Genomic Data for Modular Patterns.

Jinyu Chen1,2, Shihua Zhang1,2,3

  • 1NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, CAS, Beijing, China.

Frontiers in Genetics
|June 19, 2018
PubMed
Summary

A new MATLAB package, Matrix Integration Analysis (MIA), integrates diverse genomic data types. MIA helps identify modular biological patterns and aids researchers in selecting appropriate analysis methods.

Keywords:
bioinformaticsdata integrationmatrix integrative analysismodule discoverymulti-dimensional genomicsnon-negative matrix factorization (NMF)partial least squares (PLS)

More Related Videos

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.6K
Simple, Affordable, and Modular Patterning of Cells using DNA
08:59

Simple, Affordable, and Modular Patterning of Cells using DNA

Published on: February 24, 2021

4.7K

Related Experiment Videos

Last Updated: Feb 8, 2026

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow
12:53

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow

Published on: June 14, 2017

11.2K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.6K
Simple, Affordable, and Modular Patterning of Cells using DNA
08:59

Simple, Affordable, and Modular Patterning of Cells using DNA

Published on: February 24, 2021

4.7K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput biological data, particularly multi-dimensional genomic data, is increasingly available.
  • There is a critical need for tools that can integrate and analyze these diverse data types to understand cellular activities.

Purpose of the Study:

  • To introduce the Matrix Integration Analysis (MIA) package, a MATLAB-based tool for integrating multi-dimensional genomic data.
  • To implement and extend four established analysis methods based on non-negative matrix factorization (NMF) and partial least squares (PLS).
  • To guide users in selecting appropriate methods by highlighting the differences between NMF and PLS approaches.

Main Methods:

  • The MIA package integrates various genomic data, including copy number variation, DNA methylation, gene expression, and microRNA expression profiles.
  • It employs non-negative matrix factorization (NMF) and partial least squares (PLS) techniques.
  • The package offers an executable version for users without a MATLAB license.

Main Results:

  • MIA successfully integrates diverse genomic data to reveal underlying modular patterns.
  • The package demonstrates the distinct characteristics of NMF and PLS methods for data integration.
  • It provides a flexible framework for analyzing a wide range of biological problems and data types.

Conclusions:

  • MIA is a versatile bioinformatics tool for dissecting complex biological systems using integrated genomic data.
  • The package facilitates the identification of modular patterns and offers guidance on method selection.
  • MIA enhances accessibility to advanced genomic data integration techniques.