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dc.contributor.authorSoelter, Jan
dc.contributor.authorSchumacher, Jan
dc.contributor.authorSpors, Hartwig
dc.contributor.authorSchmuker, Michael
dc.identifier.citationSoelter , J , Schumacher , J , Spors , H & Schmuker , M 2020 , ' Computational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical map ' , Scientific Reports , no. 10 , 77 , pp. 1-16 .
dc.identifier.otherPURE: 16546234
dc.identifier.otherPURE UUID: c0789fe3-084d-40cb-a074-d298001dff14
dc.description© 2020 Springer Nature Limited.
dc.description.abstractProgress in olfaction is currently hampered by incomplete knowledge about chemical receptive ranges of primary receptors. Moreover, the chemical logic underlying the arrangement of computational units in the olfactory bulb has still not been resolved. We undertook a large-scale approach at characterising molecular receptive ranges (MRRs) of glomeruli innervated by the MOR18-2 olfactory receptor in the dorsal olfactory bulb (dOB). Guided by an iterative approach that combined biological screening and machine learning, we selected 214 odorants to characterise the response of MOR18-2 and its neighbouring glomeruli. We discovered several previously unknown odorants activating MOR18-2 glomeruli, and we obtained detailed MRRs of MOR18-2 glomeruli and their neighbours. Physico-chemical MRR descriptions revealed that the spatial layout of glomeruli follows a chemical logic. Our results confirm earlier findings that demonstrate a chemical map underlying glomerular arrangement in the dOB. Moreover, our novel methodology that combines machine learning and physiological measuremens lights the way towards future high-throughput studies to deorphan and characterise structure-activity relationships in olfaction.en
dc.relation.ispartofScientific Reports
dc.titleComputational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical mapen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre of Data Innovation Research
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review

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