Representative Proteomes for Protein Analysis
Author Information
Author(s): Chen Chuming, Natale Darren A., Finn Robert D., Huang Hongzhan, Zhang Jian, Wu Cathy H., Mazumder Raja
Primary Institution: Center for Bioinformatics and Computational Biology, University of Delaware
Hypothesis
How to select the proteomes to be included in a standard set to achieve reduced sequence space while retaining the majority of the annotation and diversity of sequences.
Conclusion
The study successfully developed a set of Representative Proteomes that significantly reduces sequence space while maintaining high levels of sequence diversity and annotation information.
Supporting Evidence
- A co-membership threshold of 55% was found to closely follow standard taxonomic classifications.
- The RP55 set retains over 95% of InterPro domains and 93% of experimentally characterized proteins.
- Using the RP set for sequence similarity searches significantly reduces computation time.
Takeaway
Scientists created a smaller set of protein data that still has all the important information, making it easier to study proteins without getting lost in too much data.
Methodology
The study developed an algorithm to calculate a hierarchical set of Representative Proteomes based on co-membership in UniRef50 clusters.
Potential Biases
Potential bias in selecting representative proteomes based on available data and existing classifications.
Limitations
The study may not account for all taxonomic classifications accurately, and some species may be misclassified.
Digital Object Identifier (DOI)
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