Steering team

Michael Schmuker (speaker), Masha Niv, Antonella di Pizio, Sebastien Fiorucci

Motivation

Olfaction and taste research depends on computational methods. Modelling structure-activity relationships for olfactory and taste receptors has become popular in recent years. Similarly, predicting the odour or taste of a molecule from its structure alone has garnered much interest. Generally, machine learning and data science techniques are commonly used in current chemosensation research, e.g., in statistical modelling, image analysis, odorant database mining, etc. Moreover, electronic olfaction and taste (“electronic noses/tongues”) are increasingly inspired by findings from biological chemosensation, with the potential of mutual inspiration and synergy between the fields.

The interdisciplinary heterogeneity of the field presents huge opportunities, but also challenges. Some researchers may work in taste, others in olfaction, some in database mining, and yet others in structure-activity-relationship prediction. While they apply similar methods, their scientific "home communities" may not overlap much; they attend different conferences and give talks at different seminars. Therefore, exchange between researchers in computational chemosensation is currently limited.

We founded the Special Interest Group "Computational Chemosensation" to overcome this limitation. We provide a common forum for researchers using computational methods in olfaction research. Our aim is to facilitate connections between researchers and to support dissemination of their research. This group is hosted under the umbrella of ECRO, the European Chemoreception Research Organisation (https://ecro.online).

Our activities include:

• Organising symposia at the ECRO annual meetings and other relevant conferences,
• Hosting online seminars about computational chemosensation,
• Widen the dissemination of computational chemosensation research, e.g., by writing collaborative review articles and editing special issues in relevant journals,
• Supporting the exchange of knowledge, techniques, and personnel between labs.

Topics

We aim to cover all aspects of computational chemosensation, including, but not limited to:

• Computational chemistry and cheminformatics, e.g., modelling structure-activity relationships, structure-odor relationships, odorant/tastant database mining,
• Data Science & Machine Learning in chemosensation research, e.g., statistical modelling, image analysis
• Bio-inspired and -mimetic designs and algorithms for electronic noses and tongues.

Want to join and get involved?

1. Fill out the membership application form and subscribe to our newsletter here: https://forms.gle/mRYSPjrzZ27L6wnXA
2. Get in touch with your ideas how the Special Interest Group could support the growth of Computational Chemosensation as a research field!