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dc.creatorRomero Zaliz, Rocíoes
dc.creatorHarari, Óscares
dc.creatorRubio Escudero, Cristinaes
dc.creatorZwir, Igores
dc.date.accessioned2022-11-30T11:41:24Z
dc.date.available2022-11-30T11:41:24Z
dc.date.issued2007
dc.identifier.citationRomero Zaliz, R., Harari, Ó., Rubio Escudero, C. y Zwir, I. (2007). Identifying the promoter features governing differential kinetics of co-regulated genes using fuzzy expressions. En FUZZ-IEEE 2007: IEEE International Conference on Fuzzy Systems (1-7), London, UK: IEEE Computer Society.
dc.identifier.isbn1-4244-1209-9es
dc.identifier.issn1098-7584es
dc.identifier.urihttps://hdl.handle.net/11441/139930
dc.description.abstractOne of the biggest challenges in genomics is the elucidation of the design principles controlling gene expression. Current approaches examine promoter sequences for particular features, such as the presence of binding sites for a transcriptional regulator, and identify recurrent relationships among these features termed network motifs. To define the expression dynamics of a group of genes, the strength of the connections in a network must be specified, and these are determined by the cis-promoter features participating in the regulation. Approaches that homogenize features among promoters (e.g., relying on consensuses to describe the various promoter features) and even across species hamper the discovery of the key differences that distinguish promoters that are co-regulated by the same transcriptional regulator. Thus, we have developed a an approach based on fuzzy logic expressions to analyze proteobacterial genomes for promoter features that is specifically designed to account for the variability in sequence, location and topology intrinsic to differential gene expression. We applied our method to characterize network motifs controlled by the PhoP/PhoQ regulatory system of Escherichia coli and Salmonella enterica serovar Typhimurium. We identify key features that enable the PhoP protein to produce distinct kinetic patterns in target genes, which could not have been uncovered just by inspecting network motifs.es
dc.formatapplication/pdfes
dc.format.extent7es
dc.language.isoenges
dc.publisherIEEE Computer Societyes
dc.relation.ispartofFUZZ-IEEE 2007: IEEE International Conference on Fuzzy Systems (2007), pp. 1-7.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleIdentifying the promoter features governing differential kinetics of co-regulated genes using fuzzy expressionses
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/4295532es
dc.identifier.doi10.1109/FUZZY.2007.4295532es
dc.contributor.groupUniversidad de Sevilla. TIC-254: Data Science and Big Data Labes
dc.publication.initialPage1es
dc.publication.endPage7es
dc.eventtitleFUZZ-IEEE 2007: IEEE International Conference on Fuzzy Systemses
dc.eventinstitutionLondon, UKes
dc.relation.publicationplaceNew York, USAes

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