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Receptors, Odorant

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Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system.

Bioinspiration & biomimetics
In many application domains, conventional e-noses are frequently outperformed in both speed and accuracy by their biological counterparts. Exploring potential bio-inspired improvements, we note a number of neuronal network models have demonstrated so...

Improving odorant chemical class prediction with multi-layer perceptrons using temporal odorant spike responses from drosophila melanogaster olfactory receptor neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work, we examine the possibility of improving the prediction performance of an olfactory biosensor through the use of temporal spiking data. We present an Artificial Neural Network (ANN), in the form of an optimal hybrid Multi-Layer Perceptro...

Numerical Models and In Vitro Assays to Study Odorant Receptors.

Methods in molecular biology (Clifton, N.J.)
Unraveling the sense of smell relies on understanding how odorant receptors recognize odorant molecules. Given the vastness of the odorant chemical space and the complexity of the odorant receptor space, computational methods are in line to propose r...

Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features.

The journal of physical chemistry letters
Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (...

Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

International journal of molecular sciences
Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulat...

Combining Machine Learning and Electrophysiology for Insect Odorant Receptor Studies.

Methods in molecular biology (Clifton, N.J.)
Insects rely on olfaction in many aspects of their life, and odorant receptors are key proteins in this process. Whereas a plethora of insect odorant receptor sequences is available, most of them are still orphan or uncompletely characterized, since ...

Computational approaches for decoding structure-saltiness enhancement and aroma perception mechanisms of odorants: From machine learning to molecular simulation.

Food research international (Ottawa, Ont.)
The unclear relationship between structure and saltiness enhancement limits the development and application of savory odorants. The structure characteristic-saltiness enhancement perception (SEP) mechanisms of savory odorants were investigated by mac...

An overview on olfaction in the biological, analytical, computational, and machine learning fields.

Archiv der Pharmazie
Recently, the comprehension of odor perception has advanced, unveiling the mysteries of the molecular receptors within the nasal passages and the intricate mechanisms governing signal transmission between these receptors, the olfactory bulb, and the ...

Insight into the Relationships Between Chemical, Protein and Functional Variables in the PBP/GOBP Family in Moths Based on Machine Learning.

International journal of molecular sciences
During their lives, insects must cope with a plethora of chemicals, of which a few will have an impact at the behavioral level. To detect these chemicals, insects use several protein families located in their main olfactory organs, the antennae. Insi...