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dc.contributor.authorHsu, CPen_US
dc.contributor.authorLee, PHen_US
dc.contributor.authorChang, CWen_US
dc.contributor.authorLee, CTen_US
dc.date.accessioned2014-12-08T15:16:30Z-
dc.date.available2014-12-08T15:16:30Z-
dc.date.issued2006-06-01en_US
dc.identifier.issn1367-4803en_US
dc.identifier.urihttp://dx.doi.org/10.1093/bioinformatics/btl082en_US
dc.identifier.urihttp://hdl.handle.net/11536/12205-
dc.description.abstractMotivation: To study biology from the systems level, mathematical models that describe the time-evolution of the system offer useful insights. Quantitative information is required for constructing such models, but such information is rarely provided. Results: We propose a scheme-based on random searches over a parameter space, according to criteria set by qualitative experimental observations-for inferring quantitative parameters from qualitative experimental results. We used five mutant constraints to construct genetic network models for sensory organ precursor formation in Drosophila development. Most of the models were capable of generating expression patterns for the gene Enhancer of split that were compatible with experimental observations for wild type and two Notch mutants. We further examined factors differentiating the neural fate among cells in a proneural cluster, and found two opposite driving forces that bias the choice between middle cells and the peripheral cells. Therefore, it is possible to build numerical models from mutant screening and to study mechanisms behind the complicated network.en_US
dc.language.isoen_USen_US
dc.titleConstructing quantitative models from qualitative mutant phenotypes: preferences in selecting sensory organ precursorsen_US
dc.typeArticleen_US
dc.identifier.doi10.1093/bioinformatics/btl082en_US
dc.identifier.journalBIOINFORMATICSen_US
dc.citation.volume22en_US
dc.citation.issue11en_US
dc.citation.spage1375en_US
dc.citation.epage1382en_US
dc.contributor.department應用化學系分子科學碩博班zh_TW
dc.contributor.departmentInstitute of Molecular scienceen_US
dc.identifier.wosnumberWOS:000238356700013-
dc.citation.woscount5-
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