Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification

scientific article published on 16 March 2021

Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1186/S13321-021-00500-8
P932PMC publication ID7962259
P698PubMed publication ID33726837

P50authorJanna HastingsQ27902110
P2093author name stringFabian Neuhaus
Till Mossakowski
Adel Memariani
Martin Glauer
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P4510describes a project that usesBayes' theoremQ182505
P433issue1
P304page(s)23
P577publication date2021-03-16
P1433published inJournal of CheminformaticsQ6294930
P1476titleLearning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification
P478volume13

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cites work (P2860)
Q115440090An impact of ontology-based service-oriented ecosystems on digital transformation of railway transport and engineering education
Q112680142From Platform to Knowledge Graph: Evolution of Laboratory Automation
Q108126975Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview
Q110391628NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products
Q113880804OARD: Open annotations for rare diseases and their phenotypes based on real-world data
Q115715393Ontologies4Chem: the landscape of ontologies in chemistry

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