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Related Concept Videos

Feedback Inhibition00:46

Feedback Inhibition

Biochemical reactions are occurring constantly in cells, converting starting substances to different products, usually with the help of enzymes that speed the reactions. Without enzymes, it would take far too long for most reactions to occur to be useful to the cell!
Cell Signaling Feedback Loops01:07

Cell Signaling Feedback Loops

Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
Negative feedback loops
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...
Positive and Negative Feedback Loops01:18

Positive and Negative Feedback Loops

Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
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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...
Feedback Loops01:01

Feedback Loops

In most cases, excessive hormone production is prevented by negative feedback—a loop that starts with a stimulus inducing the release of a particular substance, like a hormone, to maintain a certain level before triggering a signal that results in a decrease in further release of the hormone.

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Related Experiment Video

Updated: May 22, 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

WayFindR: investigating feedback in biological pathways.

Polina Bombina1, Reginald L McGee Ii2, Jake Reed3

  • 1Department of Biostatistics, Data Science, and Epidemiology, Georgia Cancer Center at Augusta University, Augusta, GA 30912, United States.

NAR Genomics and Bioinformatics
|May 21, 2026
PubMed
Summary
This summary is machine-generated.

Biological pathway analysis often misses negative feedback loops. The WayFindR R package converts pathway data into analyzable graphs, revealing these crucial regulatory features for better understanding of cellular networks.

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Understanding biological pathways is crucial for deciphering cellular functions.
  • Static pathway diagrams often fail to capture dynamic regulatory mechanisms like feedback loops.
  • Negative feedback is essential for biological system stability but is frequently underrepresented in pathway databases.

Purpose of the Study:

  • To develop a computational tool for analyzing regulatory features in biological pathways.
  • To address the underrepresentation of negative feedback loops in curated pathway data.
  • To enable the investigation of feedback regulation in cellular networks.

Main Methods:

  • Developed the WayFindR R package to convert pathway data from WikiPathways and KEGG into graph structures using the igraph library.
  • Systematically analyzed pathway information from multiple species across both databases.
  • Utilized control theory principles to identify and analyze feedback loops, particularly negative ones.

Main Results:

  • Found that feedback loops, especially negative ones, are rarely captured in current pathway databases.
  • Identified biological and technical challenges contributing to the underrepresentation of feedback mechanisms.
  • Demonstrated that WayFindR enables the computational analysis of regulatory features, including feedback loops.

Conclusions:

  • There is a significant gap in representing feedback regulation, particularly negative feedback, in biological pathway data.
  • Improved data curation and standardized annotations are necessary for a comprehensive understanding of regulatory dynamics.
  • The WayFindR package provides a scalable and reproducible method for investigating feedback regulation in cellular networks.