3.39 - Toward the Digitalization of Olfaction

Antonella Di Pizio; Jürgen Behr; Dietmar Krautwurst

doi:10.1016/B978-0-12-809324-5.24147-3

3.39 - Toward the Digitalization of Olfaction

Antonella Di Pizio (First Author), Jürgen Behr (Co-Author), Dietmar Krautwurst (Last Author)

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

7 Scopus citations

Abstract

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 language	English
Title of host publication	The Senses
Subtitle of host publication	A Comprehensive Reference: Volume 1-7, Second Edition
Publisher	Elsevier
Pages	758-768
Number of pages	11
Volume	3
ISBN (Electronic)	9780128054093
ISBN (Print)	9780128054086
DOIs	https://doi.org/10.1016/B978-0-12-809324-5.24147-3
State	Published - 1 Jan 2020

Keywords

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

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10.1016/B978-0-12-809324-5.24147-3

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title = "3.39 - Toward the Digitalization of Olfaction",

abstract = "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.",

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T1 - 3.39 - Toward the Digitalization of Olfaction

AU - Di Pizio, Antonella

AU - Behr, Jürgen

AU - Krautwurst, Dietmar

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AB - 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.

KW - Chemoreception

KW - Chemosensory

KW - Data mining

KW - Database

KW - Deep learning

KW - Digitalization

KW - Flavor

KW - GPCR

KW - Machine learning

KW - Odorant

KW - Olfaction

KW - QSOR

KW - Receptor

KW - Scent

KW - Sensor

KW - e-nose

UR - https://www.scopus.com/pages/publications/85151225234

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DO - 10.1016/B978-0-12-809324-5.24147-3

M3 - Chapter

AN - SCOPUS:85151225234

SN - 9780128054086

VL - 3

SP - 758

EP - 768

BT - The Senses

PB - Elsevier

ER -

3.39 - Toward the Digitalization of Olfaction

Abstract

Keywords

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