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Retrosynthetic analysis / Organic chemistry / Chemical reaction / Medicinal chemistry / Drug discovery / Natural product / Haloalkane / Chemical substance / Chemical compound / Chemistry / Science / Pharmaceutical sciences


Assessing Synthetic Accessibility of Chemical Compounds Using Machine Learning Methods Yevgeniy Podolyan,† Michael A. Walters,‡ and George Karypis∗,† Department of Computer Science and Computer Engineering, Unive
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Document Date: 2012-08-16 12:29:07


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Eli Lilly / Eli Lilly and Company / Molecular Design Ltd. / Sigma-Aldrich / Suzuki / InterBioScreen Ltd / /

Facility

Institute Science / MLSMR library / A library / University of Minnesota / NP library / This library / /

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chemical space / imidazo-fused ring systems / chemical synthesis / chemical reactions / breadth-first search fashion / pharmaceutical industry / decomposition search trees / physico-chemical properties / natural products / subsequent applications / dot product / chemical compounds / search tree / chemical complexity / decomposition search tree height / /

Organization

Institute for Therapeutics Discovery and Development / Chemical Compounds Using Machine Learning Methods Yevgeniy Podolyan / † Michael A. Walters / ‡ and George Karypis∗ / † Department of Computer Science and Computer Engineering / Department of Medicinal Chemistry / University of Minnesota / Minneapolis / /

Person

George Karypis / Michael A. Walters / /

Position

Route Designer / DRsvm model for synthetic accessibility prediction / /

Product

Tanimoto / /

ProvinceOrState

Minnesota / /

Technology

Drug Discovery / rational drug design / Machine Learning / /

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