HoxPred: automated classification of Hox proteins using combinations of generalised profiles
2007
HoxPred: Automated Classification of Hox Proteins
Sample size: 250
publication
Evidence: high
Author Information
Author(s): Thomas-Chollier Morgane, Leyns Luc, Ledent Valérie
Primary Institution: Université Libre de Bruxelles
Hypothesis
The study aims to develop an automated procedure to classify Hox proteins into their groups of homology.
Conclusion
HoxPred shows a mean accuracy of 97% and can efficiently contribute to large-scale automatic annotation of Hox proteins.
Supporting Evidence
- HoxPred can classify Hox proteins with a mean accuracy of 97%.
- The program is accessible via SOAP and Web interface.
- HoxPred predictions were validated against the stickleback genome assembly.
Takeaway
HoxPred is a computer program that helps scientists quickly sort Hox proteins into groups, making it easier to study them.
Methodology
The study used discriminant analysis and generalised profiles to classify Hox proteins based on a curated dataset.
Limitations
The accuracy of orthologous group predictions is lower and may require additional supporting evidence.
Digital Object Identifier (DOI)
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