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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

hiPathDB: a human-integrated pathway database with facile visualization.

Namhee Yu¹, Jihae Seo, Kyoohyoung Rho

¹Korean Bioinformation Center, KRIBB, Daejeon 305-806, Korea.

Nucleic Acids Research

|November 30, 2011

Summary

This summary is machine-generated.

hiPathDB integrates human pathway data from four major databases, organizing complex biological networks. This unified resource aids in exploring signaling pathways and identifying cross-talks for better biological network study.

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Area of Science:

Bioinformatics
Systems Biology
Computational Biology

Background:

Biological regulatory networks involve complex interactions within pathways.
Pathway information is currently fragmented across multiple databases and formats.
Systematic organization and integration of pathway data are crucial challenges.

Purpose of the Study:

To develop hiPathDB, an integrated pathway database for human biological pathways.
To combine curated pathway data from NCI-Nature PID, Reactome, BioCarta, and KEGG.
To provide tools for exploring complex biological networks and pathway cross-talks.

Main Methods:

Pathway-level integration by developing a model to reformat data from four distinct databases.
Entity-level integration to create a unified pathway by merging common components.
Development of an interactive pathway visualization module with an optimized layout algorithm.

Main Results:

hiPathDB integrates 1661 pathways comprising 8976 distinct physical entities.
Pathway and entity-level integration strategies were successfully implemented.
The visualization module facilitates interactive exploration of complex signaling networks.

Conclusions:

hiPathDB offers a unified platform for studying human biological pathways.
The integrated database facilitates the investigation of signaling networks and pathway cross-talks.
The visualization tool supports explorative analysis of complex biological networks.