http://socictopen.socict.org/files/original/3e6e30e1fca10661e44251d2f64394ed.pdf 05b6f3839f29e894224c292185f80aab Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A QSTR-Based Expert System to Predict Sweetness of Molecules Creator An entity primarily responsible for making the resource Cristian Rojas, Roberto Todeschini, Davide Ballabio, Andrea Mauri, Viviana Consonni, Piercosimo Tripaldi, Francesca Grisoni Description An account of the resource This work describes a novel approach based on advanced molecular similarity to predict the sweetness of chemicals. The proposed Quantitative Structure-Taste Relationship (QSTR) model is an expert system developed keeping in mind the five principles defined by the Organization for Economic Co-operation and Development (OECD) for the validation of (Q)SARs. The 649 sweet and non-sweet molecules were described by both conformation-independent extended-connectivity fingerprints (ECFPs) and molecular descriptors. In particular, the molecular similarity in the ECFPs space showed a clear association with molecular taste and it was exploited for model development. Molecules laying in the subspaces where the taste assignation was more difficult were modeled trough a consensus between linear and local approaches (Partial Least Squares-Discriminant Analysis and N-nearest-neighbor classifier). The expert system, which was thoroughly validated through a Monte Carlo procedure and an external set, gave satisfactory results in comparison with the state-of-the-art models. Moreover, the QSTR model can be leveraged into a greater understanding of the relationship between molecular structure and sweetness, and into the design of novel sweeteners. Date A point or period of time associated with an event in the lifecycle of the resource 2017 Subject The topic of the resource Sweetness, QSAR, molecular descriptors, classification, Expert System Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/fchem.2017.00053 Source A related resource from which the described resource is derived Frontiers in Chemistry Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chemistry Language A language of the resource EN