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Publication Date: 30 Aug 2011
Journal: Evolutionary Bioinformatics
doi: 10.4137/EBO.S7465
Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designed to provide anchor points for syntenic blocks within the Génolevures project concerning nine hemiascomycetous yeasts (about 50,000 genes) and is applicable to different input databases. Comparison based on use of a Rand index shows that the results are highly consistent with the pillars of the Yeast Gene Order Browser, a manually curated database. Compared with SYNERGY, another algorithm reporting homology relationships, our method’s main advantages are its automation and the absence of dataset-dependent parameters, facilitating consistent integration of newly released genomes.
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We have had a great experience publishing our paper in Nutrition & Metabolic Insights. The peer review process was rigorous and the journal staff were very helpful with proof processing. We will definitely be submitting future manuscripts to this journal. Keep up the good work!!Dr Sukhinder Kaur Cheema (Memorial University, St John's, Newfoundland, Canada) What Your Colleagues Say
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