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Updated: Jun 27, 2026
06:08
Automatic Identification of Dendritic Branches and their Orientation
Published on: September 17, 2021
Algorithm of OMA for large-scale orthology inference.
Alexander C J Roth1, Gaston H Gonnet, Christophe Dessimoz
1ETH Zurich, and Swiss Institute of Bioinformatics, Zurich, Switzerland. alexande@inf.ethz.ch
BMC Bioinformatics
|December 6, 2008
Summary
The OMA project identifies gene orthologs across 657 genomes using an improved algorithm. This approach enhances orthology inference by considering evolutionary distances and gene losses, offering a unique large-scale dataset.
Area of Science:
- Genomics
- Bioinformatics
- Evolutionary Biology
Background:
- The Orthologous Matrix (OMA) project focuses on identifying orthologs in publicly available, complete genomes.
- OMA has analyzed 657 genomes, establishing it as a large-scale orthology resource.
Purpose of the Study:
- To detail the OMA algorithm for orthology inference.
- To provide the rationale behind parameter selection for the OMA algorithm.
Main Methods:
- The OMA algorithm utilizes evolutionary distances, accounts for distance inference uncertainty, and includes many-to-many orthologous relations.
- It also incorporates differential gene loss into the orthology inference process.
- This method improves upon the standard bidirectional best-hit approach.
Main Results:
- The OMA algorithm offers several novel improvements for orthology inference.
- A unique, large-scale dataset of orthology assignments has been generated.
Conclusions:
- OMA presents innovative strategies for orthology inference.
- The project provides a valuable resource for large-scale comparative genomics and evolutionary studies.
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