Big Data Supervised Pairwise Ortholog Detection in Yeasts

dc.contributor.authorGalpert, Deborah
dc.contributor.authordel Río García, Sara
dc.contributor.authorHerrera, Francisco
dc.contributor.authorAncede-Gallardo, Evys
dc.contributor.authorAntunes, Agostinho
dc.contributor.authorAgüero Chapin, Guillermin
dc.coverage.spatialhttp://www.intechopen.com/books/yeast-industrial-applicationsen_US
dc.date.accessioned2023-10-25T13:45:02Z
dc.date.available2023-10-25T13:45:02Z
dc.date.issued2018-02-01
dc.description.abstractOrtholog are genes in different species, evolving from a common ancestor. Ortholog detection is essential to study phylogenies and to predict the function of unknown genes. The scalability of gene (or protein) pairwise comparisons and that of the classification process constitutes a challenge due to the ever-increasing amount of sequenced genomes. Ortholog detection algorithms, just based on sequence similarity, tend to fail in classification, specifically, in Saccharomycete yeasts with rampant paralogies and gene losses. In this book chapter, a new classification approach has been proposed based on the combination of pairwise similarity measures in a decision system that consider the extreme imbalance between ortholog and non-ortholog pairs. Some new gene pair similarity measures are defined based on protein physicochemical profiles, gene pair membership to conserved regions in related genomes, and protein lengths. The efficiency and scalability of the calculation of these measures are analyzed to propose its implementation for big data. In conclusion, evaluated supervised algorithms that manage big and imbalanced data showed high effectiveness in Saccharomycete yeast genomes.en_US
dc.identifier.doihttp://dx.doi.org/10.5772/intechopen.70479en_US
dc.identifier.urihttps://dspace.uclv.edu.cu/handle/123456789/13908
dc.language.isoen_USen_US
dc.publisherIntechOpenen_US
dc.source.endpage63en_US
dc.source.initialpage41en_US
dc.source.volumeChapter 2en_US
dc.subjectortholog detection, similarity measures, big data supervised classification, scalabilityen_US
dc.titleBig Data Supervised Pairwise Ortholog Detection in Yeastsen_US
dc.typeBook-Chapteren_US

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