SCOPUS 정보 검색 플랫폼

Molecular Informatics

Volumn 30, Issue 2-3, 2011, Pages 256-266

Predictivity of simulated ADME AutoQSAR models over time

(4) Rodgers, Sarah L a Davis, Andrew M b Tomkinson, Nick P b Van De Waterbeemd, Han c

a Accelrys Limited UK (United Kingdom)

b ASTRAZENECA (United Kingdom)

c Consultant ^* (France)

Author keywords

ADME; ADMET; AutoQSAR; BNN; PLS; Quantitative structure activity relationships (QSAR); Quantitative structure property relationships (QSPR); Random forest (RF)

Indexed keywords

BAYESIAN NETWORKS; BIOCHEMISTRY; COMPUTATIONAL CHEMISTRY; FORECASTING; MODEL BUILDINGS; MOLECULAR GRAPHICS; NEURAL NETWORKS;

ADME; ADMET; AUTOQSAR; BAYESIAN NEURAL NETWORKS; PARTIAL LEAST-SQUARES; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP; QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP; RANDOM FOREST; RANDOM FORESTS;

LEAST SQUARES APPROXIMATIONS;

AQUEOUS SOLUTION; ARTIFICIAL NEURAL NETWORK; AUTOMATION; BAYES THEOREM; CONFERENCE PAPER; LIPOPHILICITY; PH; PLASMA PROTEIN BINDING; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SIMULATION; SOLUBILITY;

EID: 79958773884 PISSN: 18681743 EISSN: 18681751 Source Type: Journal
DOI: 10.1002/minf.201000160 Document Type: Conference Paper

Times cited : (31)

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