Using Machine Learning To Predict Partition Coefficient (Log P) and Distribution Coefficient (Log D) with Molecular Descriptors and Liquid Chromatography Retention Time. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Allen_M._Y._Cheong>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/W._Scott_Hopkins>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Zaw-Myo_Win>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.1021%2Facs.jcim.2c01373>
foaf:homepage	<https://doi.org/10.1021/acs.jcim.2c01373>
dc:identifier	DBLP journals/jcisd/WinCH23 (xsd:string)
dc:identifier	DOI doi.org%2F10.1021%2Facs.jcim.2c01373 (xsd:string)
dcterms:issued	2023 (xsd:gYear)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Zaw-Myo_Win>
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swrc:number	7 (xsd:string)
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rdfs:seeAlso	<https://doi.org/10.1021/acs.jcim.2c01373>
dc:title	Using Machine Learning To Predict Partition Coefficient (Log P) and Distribution Coefficient (Log D) with Molecular Descriptors and Liquid Chromatography Retention Time. (xsd:string)
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