Prediction of natural products classes using machine learning and 13C NMR spectroscopic data

scientific article published on 15 June 2020

Prediction of natural products classes using machine learning and 13C NMR spectroscopic data is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1021/ACS.JCIM.0C00293
P698PubMed publication ID32538625

P2093author name stringGabriel Merino
Victor Uc-Cetina
María A Fernandez-Herrera
Saúl Hazel Martínez
P2860cites workNMRShiftDB - Constructing a Free Chemical Information System with Open-Source ComponentsQ27156560
Fast determination of 13C NMR chemical shifts using artificial neural networksQ30949423
Building blocks for automated elucidation of metabolites: machine learning methods for NMR predictionQ33371981
Mastering the game of Go without human knowledgeQ42209359
Recent advances in the structure elucidation of small organic molecules by the LSD softwareQ43666588
NP-StructurePredictor: Prediction of Unknown Natural Products in Plant MixturesQ47354713
New Cytotoxic Steroid Produced by the Soil-Derived Fungus Aspergillus flavus JDW-1Q105309965
P4510describes a project that usesmachine learningQ2539
P921main subjectnatural productQ901227
machine learningQ2539
P577publication date2020-06-15
P1433published inJournal of Chemical Information and ModelingQ3007982
P1476titlePrediction of natural products classes using machine learning and 13C NMR spectroscopic data

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cites work (P2860)
Q109735654Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches
Q110391829Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality
Q110391628NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products

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