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EndoNet: an information resource about the intercellular signaling network.

Jürgen Dönitz¹, Edgar Wingender

¹Institute of Bioinformatics, University Medical Center Göttingen, Goldschmidtstr, 1, 37077 Göttingen, Germany. juergen.doenitz@bioinf.med.uni-goettingen.de.

BMC Systems Biology

|April 25, 2014

Summary

EndoNet is a new database detailing the human endocrine system, including hormones, receptors, and cells. This resource aids systems biology by mapping intercellular signaling networks for better understanding of cellular interactions.

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Area of Science:

Endocrinology
Systems Biology
Bioinformatics

Background:

Multicellular organisms rely on intercellular signaling networks, primarily hormonal, to coordinate development and homeostasis.
Understanding the components and interactions within the endocrine signaling network is crucial for systems biology.
This knowledge has been historically neglected despite its importance.

Purpose of the Study:

To introduce EndoNet, a comprehensive information resource for the human endocrine system.
To provide a manually curated database of endocrine components and their relationships.
To facilitate the analysis of intercellular signaling networks within a systems biology context.

Main Methods:

EndoNet compiles data on hormones, receptors, and cells, along with their interactions (e.g., secretion, binding).
Information is manually curated from scientific literature and integrated with the Cytomer anatomical ontology.
A web interface allows users to explore components, link to external resources, and build custom networks for analysis.

Main Results:

EndoNet offers detailed information pages for each endocrine component.
Users can query related anatomical structures using the Cytomer ontology and Ontology Based Answers (OBA) service.
Customizable network analysis pipelines and export options are available.

Conclusions:

EndoNet serves as a vital and unique resource for studying the intercellular signaling network.
It provides essential data for analyzing interactions between diverse cellular networks.
The database supports advancements in systems biology by illuminating the endocrine system's role.