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Predicting Ligand Selectivity of Mammalian Odorant Receptors

dc.contributor.advisor Mukherjee, Sayan Jiang, Yue 2015-05-12T20:50:23Z 2017-04-29T04:30:04Z 2015
dc.description.abstract <p>The mammalian olfactory system uses a large family of odorant receptors to detect and discriminate amongst a myriad of volatile odor molecules. The odorant receptors are similar in protein sequence, but their ligand selectivities dramatically differ. It is not clear how the protein sequences determine the responsiveness of odorant receptors. In this study, I attempt to establish the link between the protein sequences of odorant receptors and their ligand selectivity.</p><p>Starting from the response profiles of hundreds of mouse odorant receptors to an odorant generated from my previous work, I used machine learning and variable selection methods to identify properties of amino acid residues that predict receptor response. This leads to protein sequence-based models for odorant receptor response prediction. The models trained with mouse odorant receptor data can predict human odorant receptor responses.</p>
dc.subject Statistics
dc.subject Biology
dc.subject ligand
dc.subject model
dc.subject odorant receptor
dc.title Predicting Ligand Selectivity of Mammalian Odorant Receptors
dc.type Master's thesis
dc.department Statistical Science
duke.embargo.months 23

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