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The iProClass integrated database for protein functional analysis.

Cathy H Wu¹, Hongzhan Huang, Anastasia Nikolskaya

¹Georgetown University Medical Center, Washington, DC 20057-1455, USA. wuc@georgetown.edu

Computational Biology and Chemistry

|March 17, 2004

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Scientists are using bioinformatics to study gene functions and protein properties. The iProClass database integrates system biology data for associative analysis, aiding in understanding protein evolution and function.

Area of Science:

Systems biology
Bioinformatics
Genomics

Background:

Global-scale studies of biological organization (genomes to metabolomes) are crucial for understanding complex gene functions.
New bioinformatics methods complement traditional sequence homology for inferring protein function through associative analysis.
High-throughput system biology data requires integrated bioinformatics infrastructures for data integration and associative analysis.

Purpose of the Study:

To present the iProClass database as a framework for integrating distributed system biology data.
To facilitate protein functional studies through data integration and associative analysis.
To support associative studies of protein family, domain, function, and structure using integrated data.

Main Methods:

Related Experiment Videos

Development of the iProClass database for data integration in a distributed environment.

Linking comprehensive protein descriptions to over 50 external databases (family, function, pathway, etc.).

Organizing the database with PIRSF family classification and mapping to other classification schemes.

Integrating taxonomic information for complete genomes to support associative studies.

Main Results:

iProClass provides a unified resource for protein information, linking diverse biological data.
The system supports associative studies across protein families, domains, functions, and structures.
A case study on phosphoglycerate mutases demonstrates systematic protein family and phylogenetic analysis.

Conclusions:

The iProClass database facilitates the exploitation of high-throughput system biology data.
Integrated data and associative analysis support deeper understanding of protein function and evolution.
This approach aids in studying the co-evolution of proteins, pathways, networks, and organisms.