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

24.2K
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...
24.2K
MicroRNAs01:22

MicroRNAs

4.0K
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...
4.0K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

971
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
971
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

1.6K
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
1.6K
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test01:09

Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test

6.9K
In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
6.9K
Tumor Progression02:07

Tumor Progression

7.4K
Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
7.4K

You might also read

Related Articles

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

Sort by
Same author

The microprotein SMIM26 connects metabolite transporters of the outer and inner mitochondrial membranes and is essential for respiratory chain function.

Genes & development·2026
Same author

An alginate-based 3D cell culture model as a useful tool for melanoma drug testing.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same author

A Short Report on Melanocyte/Melanoma Culture, Senescence, and Reproducibility.

Pigment cell & melanoma research·2026
Same author

In vivo AGO-APP for cell-type- and compartment-specific miRNA profiling in the mouse brain.

Cell reports methods·2025
Same author

Pachytene piRNAs define a conserved program of meiotic gene regulation: Pachytene piRNAs directly regulate select mRNAs by and RNAi-like mechanism, establishing a regulatory paradigm of mammalian meiosis.

Research square·2025
Same author

Pachytene piRNAs define a conserved program of meiotic gene regulation: Pachytene piRNAs directly regulate select mRNAs by and RNAi-like mechanism, establishing a regulatory paradigm of mammalian meiosis.

bioRxiv : the preprint server for biology·2025

Related Experiment Video

Updated: Feb 2, 2026

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
09:29

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

7.9K

MicroRNA-sequencing data analyzing melanoma development and progression.

Lisa Linck1, Janika Liebig1, Daniel Völler1

  • 1Institute of Biochemistry, Emil-Fischer-Center, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany.

Experimental and Molecular Pathology
|November 12, 2018
PubMed
Summary
This summary is machine-generated.

This study identifies 79 microRNAs (miRNAs) deregulated in melanoma development and 29 involved in cancer progression. RNA-sequencing revealed novel, strongly regulated miRNAs not previously linked to melanoma.

Keywords:
MelanomaRNA-SeqmicroRNA

More Related Videos

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells
10:55

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells

Published on: March 8, 2019

8.6K
A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

8.9K

Related Experiment Videos

Last Updated: Feb 2, 2026

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
09:29

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

7.9K
Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells
10:55

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells

Published on: March 8, 2019

8.6K
A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
06:34

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

8.9K

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • MicroRNAs (miRNAs) are increasingly recognized for their role in melanoma pathogenesis.
  • Previous studies utilized cDNA arrays for miRNA expression profiling in melanoma.

Purpose of the Study:

  • To comprehensively define the microRNAome of melanoma cell lines and primary melanocytes.
  • To identify microRNAs deregulated during melanoma development and progression using RNA-sequencing.

Main Methods:

  • RNA-sequencing (RNA-Seq) was employed to analyze miRNA expression profiles.
  • Identical cell lines used in prior cDNA array studies were re-analyzed for direct comparison.

Main Results:

  • 79 microRNAs were found to be significantly deregulated during melanoma development.
  • 29 microRNAs were identified as being involved in melanoma progression.
  • RNA-Seq identified novel, strongly regulated miRNAs not detected by cDNA arrays, expanding the understanding of melanoma-associated miRNAs.

Conclusions:

  • RNA-sequencing provides a more comprehensive and accurate view of the melanoma microRNAome compared to cDNA arrays.
  • The study identified key microRNAs critical for melanoma development and progression, offering potential diagnostic and therapeutic targets.