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ARC: automated resource classifier for agglomerative functional classification of prokaryotic proteins using
Muthiah Gnanamani1, Naveen Kumar, Srinivasan Ramachandran
1G N Ramachandran Knowledge Centre for Genome Informatics, Institute of Genomics and Integrative Biology, Mall Road, Delhi 110 007, India.
Journal of Biosciences
|October 5, 2007
Summary
Automated Resource Classifier (ARC) is a flexible, open-source software for protein functional classification. It aids comparative genomics by accurately categorizing proteins into functional classes with high success rates.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Functional classification of proteins is crucial for comparative genomics.
- Interpreting analytical data requires flexible, automated algorithms.
- A general, automated software solution is needed to aid this process.
Purpose of the Study:
- To develop ARC (Automated Resource Classifier), an open-source software for flexible protein functional classification.
- To provide a general, automated tool for integrative interpretation of analytical data in genomics.
Main Methods:
- ARC utilizes a keyword-matching, agglomerative classification scheme.
- The keyword library was built using data from Bacillus subtilis, Escherichia coli K12, Archaeoglobus fulgidus, Gene Ontology, and Gene Symbols.
- The software classifies proteins into 7 basic and 2 ancillary functional classes.
Main Results:
- ARC achieved 94.04% success on 675,663 annotated proteins from 348 prokaryotes.
- The software demonstrates flexibility and meets user requirements.
- Examples illustrate its application in understanding mycobacterial physiology and protein costs.
Conclusions:
- ARC is a highly successful and flexible tool for automated protein functional classification.
- The software significantly aids comparative genomics and data interpretation.
- ARC is publicly available for researchers.
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