ArticlePloS one2015
Understanding the Odour Spaces: A Step towards Solving Olfactory Stimulus-Percept Problem.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Deep Learning for Odor Prediction on Aroma-Chemical Blends.ACS omega · 2025Article
- Data-Driven Elucidation of Flavor Chemistry.Journal of agricultural and food chemistry · 2023Review
- OWSum: algorithmic odor prediction and insight into structure-odor relationships.Journal of cheminformatics · 2023Article
- Olfactory abstraction: a communicative and metacognitive account.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- OOPS, the Ontology for Odor Perceptual Space: From Molecular Composition to Sensory Attributes of Odor Objects.Molecules (Basel, Switzerland) · 2022Article
- More than meets the AI: The possibilities and limits of machine learning in olfaction.Frontiers in neuroscience · 2022Review
- Chemical features mining provides new descriptive structure-odor relationships.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Odours are highly complex, relying on hundreds of receptors, and people are known to disagree in their linguistic descriptions of smells. It is partly due to these facts that, it is very hard to map the domain of odour molecules or their structure to that of perceptual representations, a problem that has been referred to as the Structure-Odour-Relationship. We collected a number of diverse open domain databases of odour molecules having unorganised perceptual descriptors, and developed a graphical method to find the similarity between perceptual descriptors; which is intuitive and can be used to identify perceptual classes. We then separately projected the physico-chemical and perceptual features of these molecules in a non-linear dimension and clustered the similar molecules. We found a significant overlap between the spatial positioning of the clustered molecules in the physico-chemical and perceptual spaces. We also developed a statistical method of predicting the perceptual qualities of a novel molecule using its physico-chemical properties with high receiver operating characteristics(ROC).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.