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

Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

7.4K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
7.4K
Hedgehog Signaling Pathway02:33

Hedgehog Signaling Pathway

10.2K
The Hedgehog gene (Hh) was first discovered due to its control of the growth of disorganized, hair-like bristles phenotype in Drosophila, much like hedgehog spines. Hh plays a crucial role in the development of organs and the maintenance of homeostasis in both invertebrates and vertebrates. However, while Drosophila has only one Hh protein, mammals have multiple functional Hedgehog proteins - Sonic (Shh), Desert (Dhh), and Indian Hedgehog (Ihh). All of these homologous proteins have adapted to...
10.2K
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

18.7K
When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
18.7K
IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

15.2K
Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the  phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and...
15.2K
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

8.0K
The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...
8.0K
Signal Flow Graphs01:18

Signal Flow Graphs

675
Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
675

You might also read

Related Articles

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

Sort by
Same author

Provenance Tracing in Network Diffusion Algorithms.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same author

SynVerse: a modular framework for building and evaluating deep learning-based drug synergy prediction models.

Briefings in bioinformatics·2025
Same author

ProteinWeaver: A webtool to visualize ontology-annotated protein networks.

PloS one·2025
Same author

GRPhIN: graphlet characterization of regulatory and physical interaction networks.

Bioinformatics advances·2025
Same author

NEFFy: a versatile tool for computing the number of effective sequences.

Bioinformatics (Oxford, England)·2025
Same author

CNB-MAC 2023 Special Issue.

Journal of computational biology : a journal of computational molecular cell biology·2025
Same journal

circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Hierarchical Hypergraph Learning in Association- Weighted Heterogeneous Network for miRNA- Disease Association Identification.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Discriminative Domain Adaption Network for Simultaneously Removing Batch Effects and Annotating Cell Types in Single-Cell RNA-Seq.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

MLW-BFECF: A Multi-Weighted Dynamic Cascade Forest Based on Bilinear Feature Extraction for Predicting the Stage of Kidney Renal Clear Cell Carcinoma on Multi-Modal Gene Data.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Generative Biomedical Event Extraction With Constrained Decoding Strategy.

IEEE/ACM transactions on computational biology and bioinformatics·2024
See all related articles

Related Experiment Video

Updated: Feb 21, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

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

Published on: July 1, 2020

3.8K

Pathway Analysis with Signaling Hypergraphs.

Anna Ritz, Brendan Avent, T M Murali

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |October 10, 2017
    PubMed
    Summary
    This summary is machine-generated.

    Signaling pathways are better modeled using novel signaling hypergraphs, not traditional graphs. This new method identifies essential proteins and interactions for specific cellular responses, offering more informative results than existing approaches.

    More Related Videos

    A Web Tool for Generating High Quality Machine-readable Biological Pathways
    08:01

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

    Published on: February 8, 2017

    18.6K
    Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
    09:47

    Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

    Published on: December 15, 2023

    1.9K

    Related Experiment Videos

    Last Updated: Feb 21, 2026

    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
    05:01

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

    Published on: July 1, 2020

    3.8K
    A Web Tool for Generating High Quality Machine-readable Biological Pathways
    08:01

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

    Published on: February 8, 2017

    18.6K
    Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
    09:47

    Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

    Published on: December 15, 2023

    1.9K

    Area of Science:

    • Computational Biology
    • Systems Biology
    • Graph Theory

    Background:

    • Signaling pathways regulate cellular responses to environmental stimuli.
    • Traditional directed graphs inadequately represent complex biological reactions like protein assembly and combinatorial regulation.
    • Directed hypergraphs offer a more accurate representation but are underutilized in biological modeling.

    Purpose of the Study:

    • To introduce signaling hypergraphs, an extension of directed hypergraphs, for improved modeling of biological signaling pathways.
    • To formulate and solve the problem of identifying essential components for specific downstream signaling responses.
    • To demonstrate the superiority of signaling hypergraphs over traditional graph-based methods in biological pathway analysis.

    Main Methods:

    • Developed the concept of a signaling hypergraph, an extension of directed hypergraphs.
    • Formulated a problem to find essential proteins and interactions for a specific signaling outcome.
    • Related this problem to computing shortest acyclic B-hyperpaths, an NP-hard problem.
    • Implemented a mixed integer linear program to solve the shortest hyperpath problem.

    Main Results:

    • Signaling hypergraphs provide a more accurate representation of complex signaling events.
    • Shortest hyperpaths in signaling hypergraphs yield more informative results than shortest paths or Steiner trees in graph representations.
    • Computed shortest hyperpaths revealed crucial proteins and interactions for specific pathway responses.

    Conclusions:

    • Signaling hypergraphs represent a powerful tool for analyzing biological signaling pathways.
    • This approach offers significant advantages over traditional graph-based methods for understanding complex cellular processes.
    • Further development of hypergraph algorithms is warranted to fully leverage their potential in systems biology.