Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein Networks

Protein Networks

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

C4 Pathway and CAM

C4 Pathway and CAM

Most plants use the C3 pathway for carbon fixation. However, some plants, such as sugar cane, corn, and cacti that grow in hot conditions, use alternative pathways to fix carbon and conserve energy loss due to photorespiration. Photorespiration is the process that occurs when the oxygen concentration is high. Under such conditions, the rubisco enzyme in the Calvin cycle binds O2 instead of CO2, which halts photosynthesis and consumes energy.
C4 Pathway
The C4 pathway is used by plants such as...

You might also read

Related Articles

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

Sort by

Same author

Relationship between persistent atrial fibrillation in high-altitude regions and left atrial diameter, red cell distribution width, and NT-ProBNP: a retrospective case-control study.

Frontiers in cardiovascular medicine·2026

Same author

Plant-based diet, metabolic signature, genetic susceptibility, and risk of musculoskeletal disorders: a large-scale population-based prospective cohort study.

Frontiers in public health·2026

Same author

A multi-trait polygenic risk score enhances osteoporosis risk prediction in East Asian population.

Journal of advanced research·2026

Same author

Loneliness, traditional risk factor control, genetic predisposition, and development of musculoskeletal disorders.

Rheumatology (Oxford, England)·2026

Same author

Design, Synthesis, and Evaluation of Bibenzyl Analogues against Hepatocellular Carcinoma by Targeting Pyruvate Carboxylase.

Journal of medicinal chemistry·2026

Same author

Tumor treating fields in malignant pleural mesothelioma: from cytoskeletal collapse to immunophenotypic conversion.

Frontiers in immunology·2026

Search research articles

Related Experiment Video

Updated: Feb 22, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

New tools for the visualization of biological pathways.

Tomojit Ghosh¹, Xiaofeng Ma¹, Michael Kirby¹

¹Colorado State University, Fort Collins, CO, USA.

Methods (San Diego, Calif.)

|September 19, 2017

Summary

New geometric methods effectively visualize complex, high-dimensional biological data, outperforming traditional techniques like principal component analysis for gene expression analysis. These approaches reveal crucial data structures in lower dimensions, aiding in understanding immune responses.

Keywords:

Autoencoder Centroid-encoder Data visualization Ebola virus Grassmannian embedding Sparse radial basis functions

More Related Videos

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

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

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

Published on: December 7, 2021

Related Experiment Videos

Last Updated: Feb 22, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

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

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

Published on: December 7, 2021

Area of Science:

Computational Biology
Data Visualization
Bioinformatics

Background:

High-dimensional biological data, such as gene expression, presents visualization challenges.
Traditional methods like principal component analysis (PCA) may fail when data variance spans multiple dimensions.

Purpose of the Study:

To introduce novel, geometrically motivated techniques for visualizing high-dimensional biological data.
To demonstrate the effectiveness of these methods compared to existing approaches.

Main Methods:

Utilizing the Grassmann manifold for subspace data similarity.
Employing sparse radial basis function classification via convex optimization.
Introducing supervised centroid-encoding inspired by deep belief networks.

Main Results:

Proposed methods successfully capture significant data structure in 2-3 dimensions.
These techniques outperform linear and nonlinear PCA for visualization when data variance is spread.
Applied to Ebola virus infection gene expression data in primates and mice.

Conclusions:

Geometrically motivated techniques offer superior visualization of high-dimensional biological data.
These methods enhance the understanding of complex biological systems, like immune responses to infection.