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Related Experiment Video

Updated: May 27, 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

IPAVS: Integrated Pathway Resources, Analysis and Visualization System.

Pradeep Kumar Sreenivasaiah¹, Shilpa Rani, Joseph Cayetano

¹School of Life Sciences and Systems Biology Research Center, Gwangju Institute of Science and Technology, Gwangju 500-712, Korea.

Nucleic Acids Research

|December 6, 2011

Summary

This summary is machine-generated.

The Integrated Pathway Resources, Analysis and Visualization System (iPAVS) offers a comprehensive database for biological pathway discovery. It provides expert-curated pathways and analysis tools for systems biology research.

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Area of Science:

Systems Biology
Bioinformatics
Genomics

Background:

Biological pathway databases are crucial for understanding complex cellular processes.
Existing resources often lack integration and context-specific curation.
Biologists require accessible tools for pathway discovery and data interpretation.

Purpose of the Study:

To introduce the Integrated Pathway Resources, Analysis and Visualization System (iPAVS) as a novel biological pathway database.
To support pathway discovery across proteomics, transcriptomics, metabolomics, and systems biology.
To provide context-specific, expert-curated pathways for biological research.

Main Methods:

Integration of over 500 human pathways and 24,574 interactions.
Development of a web interface for browsing, searching, and data analysis.
Utilization of Systems Biology Graphical Notations (SBGN) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for visualization.
Provision of downloadable datasets in standard formats.

Main Results:

iPAVS integrates diverse pathway types including metabolic, signaling, disease-related, and drug-action pathways.
The system facilitates data import, management, visualization, and analysis.
Expert-curated pathways are linked to specific biological contexts like cell types, tissues, organs, and diseases.

Conclusions:

iPAVS enhances biological data interpretation by providing integrated, context-specific pathway resources.
The system empowers biologists with tools for comprehensive pathway discovery and analysis.
iPAVS serves as a valuable resource for advancing systems biology research.