3.39 - Toward the Digitalization of Olfaction

Antonella Di Pizio, Jürgen Behr, Dietmar Krautwurst

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

6 Scopus citations


Technical advancements are leading to a rapid increase of odorant-centered and receptor-based olfaction data, while at the same creating the necessity to establish olfaction-centered, data mining-capable databases. Digitalizing data allows a faster data processing, and thus will be essential to decode the complexity of the molecular mechanisms in olfaction, to finally enable reproducible and applicable digital representations of olfactory percepts. In this chapter, we review state-of-the-art techniques and available data sources in olfaction, highlighting the potential impact of data digital transformation in the field of olfaction.

Original languageEnglish
Title of host publicationThe Senses
Subtitle of host publicationA Comprehensive Reference: Volume 1-7, Second Edition
Number of pages11
ISBN (Electronic)9780128054093
ISBN (Print)9780128054086
StatePublished - 1 Jan 2020
Externally publishedYes


  • Chemoreception
  • Chemosensory
  • Data mining
  • Database
  • Deep learning
  • Digitalization
  • Flavor
  • GPCR
  • Machine learning
  • Odorant
  • Olfaction
  • QSOR
  • Receptor
  • Scent
  • Sensor
  • e-nose


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