AIMC Topic: Taste

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Classification of tastants: A deep learning based approach.

Molecular informatics
Predicting the taste of molecules is of critical importance in the food and beverages, flavor, and pharmaceutical industries for the design and screening of new tastants. In this work, we have built deep learning models to classify sweet, bitter, and...

A TastePeptides-Meta system including an umami/bitter classification model Umami_YYDS, a TastePeptidesDB database and an open-source package Auto_Taste_ML.

Food chemistry
Taste peptides with umami/bitterness play a role in food attributes. However, the taste mechanisms of peptides are not fully understood, and the identification of these peptides is time-consuming. Here, we created a taste peptide database by collecti...

Premexotac: Machine learning bitterants predictor for advancing pharmaceutical development.

International journal of pharmaceutics
Bitter taste receptors were recently found to be involved in numerous physiological and pathological conditions other than taste and are suggested as potential drug targets. In vivo and in vitro techniques for screening bitterants as ligands come wit...

Effect of short-term frozen storage on taste of gonads of female Eriocheir sinensis and the classification of taste quality combined with sensory evaluation and fuzzy logic model.

Food chemistry
To investigate the taste quality of gonads of Eriocheir sinensis during frozen storage, the difference in overall taste profile was determined by electronic tongue, and the contents of free amino acids and 5'-Nucleotides were measure. The results sho...

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning.

International journal of molecular sciences
Umami ingredients have been identified as important factors in food seasoning and production. Traditional experimental methods for characterizing peptides exhibiting umami sensory properties (umami peptides) are time-consuming, laborious, and costly....

CBDPS 1.0: A Python GUI Application for Machine Learning Models to Predict Bitter-Tasting Children's Oral Medicines.

Chemical & pharmaceutical bulletin
Bitter tastes are innately aversive and are thought to help protect animals from consuming poisons. Children are extremely sensitive to drug tastes, and their compliance is especially poor with bitter medicine. Therefore, judging whether a drug is bi...

iBitter-Fuse: A Novel Sequence-Based Bitter Peptide Predictor by Fusing Multi-View Features.

International journal of molecular sciences
Accurate identification of bitter peptides is of great importance for better understanding their biochemical and biophysical properties. To date, machine learning-based methods have become effective approaches for providing a good avenue for identify...

Prediction of specialty coffee flavors based on near-infrared spectra using machine- and deep-learning methods.

Journal of the science of food and agriculture
BACKGROUND: Specialty coffee fascinates people with its bountiful flavors. Currently, flavor descriptions of specialty coffee beans are only offered by certified coffee cuppers. However, such professionals are rare, and the market demand is tremendou...

Bioinspired multisensory neural network with crossmodal integration and recognition.

Nature communications
The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation...

Effect of cross-cultural differences on thickness, firmness and sweetness sensitivity.

Food research international (Ottawa, Ont.)
Sensitivity of the somatosensory system may be influenced by multiple physiological parameters. Variations in oral physiology can arise from cross-cultural differences which may potentially affect sensory sensitivity. The aim of this case study was t...