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

MicroRNAs01:22

MicroRNAs

24.3K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After...
24.3K
MicroRNAs01:22

MicroRNAs

4.1K
MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
4.1K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

815
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...
815
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.7K
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...
1.7K
DNA Microarrays02:34

DNA Microarrays

21.3K
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...
21.3K
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

Mucin alleviates HFD-induced obesity and MASLD via an Akkermansia muciniphila-associated mucin-Neu5Ac-PPARα signaling axis.

Pharmacological research·2026
Same author

KAZN methylation as a potential diagnostic and prognostic marker in non-small cell lung cancer.

iScience·2025
Same author

Diabetes is causally associated with increased breast cancer mortality by inducing FIBCD1 to activate MCM5-mediated cell cycle arrest via modulating H3K27ac.

Cell death & disease·2025
Same author

Exposure to polycyclic aromatic hydrocarbons and risk of abnormal liver function: The mediating role of C-reactive protein.

Ecotoxicology and environmental safety·2025
Same author

Downregulation of tRNA methyltransferase FTSJ1 by PM2.5 promotes glycolysis and malignancy of NSCLC via facilitating PGK1 expression and translation.

Cell death & disease·2024
Same author

MDM2 Is Essential to Maintain the Homeostasis of Epithelial Cells by Targeting p53.

Journal of innate immunity·2024
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

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

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

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

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

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

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

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

Characterization of Bioactive Saponins from Sea Cucumbers.

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

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

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

Related Experiment Video

Updated: Feb 13, 2026

Performing Custom MicroRNA Microarray Experiments
07:04

Performing Custom MicroRNA Microarray Experiments

Published on: October 28, 2011

20.0K

Microarray-Based MicroRNA Expression Data Analysis with Bioconductor.

Emilio Mastriani1,2, Rihong Zhai3, Songling Zhu4,5

  • 1Systemomics Center, College of Pharmacy, Harbin Medical University, Harbin, China.

Methods in Molecular Biology (Clifton, N.J.)
|March 7, 2018
PubMed
Summary
This summary is machine-generated.

This study presents a standard pipeline for analyzing microRNA (miRNA) microarray data using R and Bioconductor. It outlines key steps for identifying disease-associated molecular signatures and understanding miRNA functions.

Keywords:
BioconcductorGene expression analysisMicroRNA (miRNA)Microarray data analysisR Package

More Related Videos

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
Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish
11:42

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

11.5K

Related Experiment Videos

Last Updated: Feb 13, 2026

Performing Custom MicroRNA Microarray Experiments
07:04

Performing Custom MicroRNA Microarray Experiments

Published on: October 28, 2011

20.0K
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
Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish
11:42

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

11.5K

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • MicroRNAs (miRNAs) are crucial regulators of gene expression, but their functions are largely unannotated.
  • Microarray analysis offers a cost-effective method for identifying candidate miRNAs linked to biological pathways and disease signatures.

Purpose of the Study:

  • To present a standardized analysis pipeline for miRNA microarray data.
  • To facilitate the functional annotation and disease association studies of microRNAs.

Main Methods:

  • The pipeline integrates established R packages from the Bioconductor project.
  • It covers essential steps: quality control, normalization, differential expression analysis, target gene prediction, and functional annotation.

Main Results:

  • A reproducible and accessible workflow for miRNA microarray data analysis is provided.
  • The pipeline enables the identification of significant molecular signatures and potential miRNA biomarkers.

Conclusions:

  • The presented pipeline offers a robust framework for researchers to analyze miRNA expression data.
  • It supports the advancement of understanding miRNA roles in biological processes and diseases.