The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling.

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander.

Afiliación

Khashan R; Department Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Al-Ahsa, KSA 31982 phone: +966-13-581-7175; fax: +966-13-581-7174. rkhashan@kfu.edu.sa.
Zheng W; Biomanufacturing Research Institute & Technology Enterprise, NCCU, Durham, NC 27707, USA.
Tropsha A; Laboratory for Molecular Modeling and Carolina Center for Exploratory Cheminformatics Research, School of Pharmacy, UNC, Chapel Hill, NC 27599, USA.

Mol Inform ; 33(3): 201-15, 2014 Mar.

Article en En | MEDLINE | ID: mdl-27485689

Palabras clave

Chemical fragment-based descriptors; Fast frequent subgraph mining; Two-dimensional descriptors; k-Nearest neighbor QSAR techniques

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Mol Inform Año: 2014 Tipo del documento: Article

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