Quantitative structure-activity relationships (QSARs) using the novel marine algal toxicity data of phenols

Journal of Molecular Graphics and Modelling

Volumn 38, Issue , 2012, Pages 90-100

  Ertürk, M Doǧa ^a   Saçan, Melek Türker ^a   Novic, Marjana ^b   Minovski, Nikola ^b  

^a BOGAZICI UNIVERSITY   (Turkey)

^b NATIONAL INSTITUTE OF CHEMISTRY   (Slovenia)

Author keywords

CPANN; Marine alga; MLR; Phenols; QSAR; Toxicity

Indexed keywords

ALGAL TOXICITY; ATOMIC POLARIZABILITY; COUNTER PROPAGATION; CPANN; DATA SETS; DESCRIPTORS; DUNALIELLA; FRESHWATER ALGAE; GLOBAL MODELS; MARINE ALGAE; MLR; MODELING PROCESS; MULTIPLE LINEAR REGRESSIONS; OCTANOL/WATER PARTITION COEFFICIENT; PHENOLIC COMPOUNDS; POLAR NARCOTICS; PREDICTION ACCURACY; PREDICTIVITY; PSEUDOKIRCHNERIELLA SUBCAPITATA; QSAR; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS; REACTIVE MECHANISM; TEST SETS; TOXICITY DATA; UNCOUPLERS;

ALCOHOLS; ALGAE; COMPUTATIONAL CHEMISTRY; DYES; LINEAR REGRESSION; NEURAL NETWORKS; ORGANIC CHEMICALS; TOXICITY;

PHENOLS;

HYDROQUINONE; OCTANOL; PHENOL; WATER;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; DUNALIELLA TERTIOLECTA; HYDROPHOBICITY; MOLECULAR MODEL; MULTIPLE LINEAR REGRESSION ANALYSIS; PARTITION COEFFICIENT; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; TOXICITY TESTING;

AQUATIC ORGANISMS; CHLOROPHYTA; HYDROPHOBIC AND HYDROPHILIC INTERACTIONS; HYDROQUINONES; LINEAR MODELS; NARCOTICS; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; STATIC ELECTRICITY; UNCOUPLING AGENTS;

ALGAE; DUNALIELLA TERTIOLECTA; SELENASTRUM CAPRICORNUTUM;

EID: 84867440911     PISSN: 10933263     EISSN: 18734243     Source Type: Journal    
DOI: 10.1016/j.jmgm.2012.06.002     Document Type: Article

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