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Related Concept Videos

Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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...
IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

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 produces two-second...
Hedgehog Signaling Pathway02:33

Hedgehog Signaling Pathway

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...
Hedgehog Signaling Pathway02:33

Hedgehog Signaling Pathway

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...
The JAK-STAT Signaling Pathway01:20

The JAK-STAT Signaling Pathway

Several cytokine receptors have tightly bound Janus kinase or JAK proteins attached at their cytosolic tail. Small signaling molecules such as cytokines, growth hormones, or prolactins bind to the cytokine receptors and initiate their dimerization. The dimerization brings the cytosolic JAKs together that trans-phosphorylate and activates each other. The activated JAKs now phosphorylate cytosolic tails of the cytokine receptors, which serve as binding sites for adaptor proteins such as  SH2...
Intracellular Signaling Cascades01:24

Intracellular Signaling Cascades

Once a ligand binds to a receptor, the signal is transmitted through the membrane and into the cytoplasm. The continuation of a signal in this manner is called signal transduction. Signal transduction only occurs with cell-surface receptors, which cannot interact with most components of the cell, such as DNA. Only internal receptors can interact directly with DNA in the nucleus to initiate protein synthesis. When a ligand binds to its receptor, conformational changes occur that affect the...

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Related Experiment Video

Updated: May 8, 2026

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

Signalling pathway database usability: lessons learned.

Paolo Tieri1, Christine Nardini

  • 1Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Yue Yang Road 320, Shanghai, P. R. China.

Molecular Biosystems
|August 15, 2013
PubMed
Summary
This summary is machine-generated.

Signalling pathway databases show significant variations in data quality and quantity, impacting research. Evaluating database coherence is crucial for reliable in silico biology and accurate experimental validation.

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Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing
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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
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Last Updated: May 8, 2026

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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Signalling pathway databases are essential for research but suffer from accessibility, understandability, and usability issues.
  • These limitations can disrupt research workflows and lead to misinterpretation of results.
  • Six major databases (Reactome, Pathway Commons, KEGG, InnateDB, PID, Wikipathways) were analyzed for signalling pathway data.

Purpose of the Study:

  • To assess the variations in data quality and quantity across major curated signalling pathway databases.
  • To identify objective criteria for selecting the most reliable data sources.
  • To provide recommendations for improving database usability and data coherence.

Main Methods:

  • Querying and analyzing results from six leading curated signalling pathway databases for a specific set of test genes.
  • Evaluating data variations based on database design, data types, query structure, and search procedure descriptions.
  • Quantifying inner and cross coherence as objective criteria for database selection.

Main Results:

  • Observed significant and exceptional variations in the quality and quantity of results across databases.
  • Differences attributed to diverse database designs, purposes, data types, query structures, and search descriptions.
  • Identified inner and cross coherence as quantifiable features for assessing database reliability.

Conclusions:

  • In silico biology relies heavily on database information; data codification coherence is critical but underestimated.
  • Ensuring database coherence is vital for computational biology to accurately reflect biological reality.
  • Recommendations are provided for end-users and database maintainers to improve data quality and support open data principles.