Novel scaffold of natural compound eliciting sweet taste revealed by machine learning

Food Chemistry

Volumn 324, Issue , 2020, Pages

  Bouysset, Cédric ^a   Belloir, Christine ^b   Antonczak, Serge ^a   Briand, Loïc ^b   Fiorucci, Sébastien ^a  

^a UNIVERSITÉ CÔTE D'AZUR   (France)

^b CENTRE DES SCIENCES DU GOÛT ET DE L ALIMENTATION   (France)

Author keywords

Machine learning; Natural compounds; Sweet taste; Sweet taste receptor; Sweetener

Indexed keywords

SCAFFOLDS (BIOLOGY); SUGAR INDUSTRY;

CHEMICAL FAMILY; CHEMICAL SPACE; FOOD INDUSTRIES; FUNCTIONAL ASSAYS; MACHINE LEARNING MODELS; MOLECULAR FEATURE; NATURAL COMPOUNDS; OPEN SOURCES;

MACHINE LEARNING;

ARCTIIN; GINSENOSIDE RD; JUJUBOSIDE A; LIGNAN; NATURAL PRODUCT; POLYPHENOL; SUCRALOSE; SUCROSE; SUGAR; SWEETENING AGENT; UNCLASSIFIED DRUG; G PROTEIN COUPLED RECEPTOR;

ARTICLE; ASSAY; CHEMICAL STRUCTURE; COMPUTER MODEL; CONSUMER; FLAVOR; HUMAN; MACHINE LEARNING; PERCEPTION; PLANT; PREDICTION; SENSORY RECEPTOR; SWEETNESS; TASTE; TASTE BUD; METABOLISM; PHYSIOLOGY;

HUMANS; MACHINE LEARNING; RECEPTORS, G-PROTEIN-COUPLED; SWEETENING AGENTS; TASTE;

EID: 85083701629     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2020.126864     Document Type: Article

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