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

Interpreting R Charts01:22

Interpreting R Charts

373
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
373
Molecular Models02:00

Molecular Models

44.0K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
44.0K
pV-Diagrams01:18

pV-Diagrams

6.3K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
6.3K
Multiple Bar Graph01:07

Multiple Bar Graph

10.3K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
10.3K
Overview of Minitab01:11

Overview of Minitab

746
Minitab is a statistical software package designed for data analysis. With its origins in the 1970s and development at Pennsylvania State University, Minitab has grown significantly in its capabilities and applications. It plays a crucial role in quality management projects, especially in Six Sigma initiatives, by offering tools for process improvement and statistical analysis. Minitab's significance lies in its user-friendly interface, making complex statistical analysis accessible to...
746
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

5.7K
The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
5.7K

You might also read

Related Articles

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

Sort by
Same author

Efficacy and safety of neoadjuvant apatinib plus PD-1 inhibitor with SOX for locally advanced gastric cancer: A multicenter, retrospective cohort study.

International journal of cancer·2026
Same author

Entropy Production in Non-Gaussian Active Matter: A Unified Fluctuation Theorem and Deep Learning Framework.

Physical review letters·2026
Same author

Effect of whole-course nutrition management on skeletal muscle mass in patients with gastric cancer undergoing neoadjuvant treatment.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology·2026
Same author

<i>STAT3<sup>R152W</sup></i> Mutation Model Reveals Temporal Changes in Hematopoietic Populations.

International journal of molecular sciences·2026
Same author

Chromatin modifiers KMT2D, BAF, and p300 are required for <i>de novo</i> binding of transcription factors on enhancers.

bioRxiv : the preprint server for biology·2026
Same author

Non-contact seismocardiogram measurement and HRV analysis using cardiac beamforming with FMCW radar.

Frontiers in physiology·2026

Related Experiment Video

Updated: Feb 18, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Dynamic visualization of multi-level molecular data: The Director package in R.

Katherine Icay1, Chengyu Liu1, Sampsa Hautaniemi1

  • 1Research Programs Unit, Genome-Scale Biology, Faculty of Medicine, University of Helsinki, Helsinki, POB 63, 00014, Finland.

Computer Methods and Programs in Biomedicine
|November 22, 2017
PubMed
Summary

The R package Director visualizes multi-omics cancer data, revealing microRNA-gene interactions and extracellular matrix roles in ovarian cancer prognosis. This tool aids in identifying actionable insights from complex molecular datasets.

More Related Videos

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
06:01

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

Published on: December 12, 2019

9.0K
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
10:10

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

41.7K

Related Experiment Videos

Last Updated: Feb 18, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K
Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
06:01

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

Published on: December 12, 2019

9.0K
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
10:10

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

41.7K

Area of Science:

  • Bioinformatics
  • Genomics
  • Systems Biology

Background:

  • High-throughput technologies generate vast multi-omics cancer data.
  • Analyzing and interpreting this data for clinical insights remains challenging.
  • Existing methods often lack effective post-analysis interpretation tools.

Purpose of the Study:

  • To introduce the R package Director for dynamic visualization of multi-omics data.
  • To link and interrogate multiple molecular data levels for actionable insights.
  • To enhance data interpretation in large-scale cancer studies.

Main Methods:

  • Utilizes Sankey diagrams to represent biological information flow as regulatory cascades.
  • Adapts Sankey diagrams for quantitative measures and molecular interactions.
  • Streamlines diagram creation from quantitative measurements of molecules and interactions.

Main Results:

  • Demonstrates utility with ovarian cancer microRNA-gene networks.
  • Reveals potential co-regulatory behavior in the extracellular matrix (ECM).
  • Identifies molecular signatures associated with poor prognosis, including elevated metastasis-associated genes and decreased targeting microRNAs.

Conclusions:

  • Director provides a visualization approach for multi-omics data analysis workflows.
  • Facilitates novel perspectives on candidate biomarkers in complex diseases.
  • Offers dynamic, shareable, and cross-platform compatible visualizations via HTML output.