Predicting Ligand Selectivity of Mammalian Odorant Receptors

dc.contributor.advisor

Mukherjee, Sayan

dc.contributor.author

Jiang, Yue

dc.date.accessioned

2015-05-12T20:50:23Z

dc.date.available

2017-04-29T04:30:04Z

dc.date.issued

2015

dc.department

Statistical Science

dc.description.abstract

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.

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.

dc.identifier.uri

https://hdl.handle.net/10161/9992

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

duke.embargo.months

23

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Jiang_duke_0066N_12845.pdf
Size:
6.37 MB
Format:
Adobe Portable Document Format

Collections