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dc.creatorDougherty, Edward R.
dc.creatorKim, Seungchan
dc.creatorBittner, Michael L.
dc.creatorChen, Yidong
dc.date.accessioned2019-06-17T17:00:20Z
dc.date.available2019-06-17T17:00:20Z
dc.date.issued2006-02-21
dc.identifier.urihttp://hdl.handle.net/1969.1/176810
dc.description.abstractRelatedness between genes is quantified by constructing nonlinear models predicting gene expression. Effectiveness of the model is evaluated to provide a measurement of the relatedness of genes associated with the model. Various types of models, including full-logic or neural networks can be constructed. A graphical user interface presents results of the analysis to allow evaluation by a user. Each gene's contribution to the measurement of relatedness can be shown on a graph, and graphical representations of models used to predict gene expression can be displayed.en
dc.languageeng
dc.publisherUnited States. Patent and Trademark Office
dc.rightsPublic Domain (No copyright - United States)en
dc.rights.urihttp://rightsstatements.org/vocab/NoC-US/1.0/
dc.titleQuantifying gene relatedness via nonlinear prediction of geneen
dc.typeUtility patenten
dc.format.digitalOriginreformatted digitalen
dc.description.countryUS
dc.contributor.assigneeThe United States of America as represented by the Department of Health and Human Services
dc.contributor.assigneeThe Texas A & M University System
dc.identifier.patentapplicationnumber09/595580
dc.subject.uspcprimary702/19
dc.subject.uspcother435/6.13
dc.subject.uspcother702/20
dc.subject.uspcother706/15
dc.subject.uspcother706/21
dc.date.filed2000-06-15
dc.publisher.digitalTexas A&M University. Libraries


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