QSAR models for prediction of PPARδ agonistic activity of indanylacetic acid derivatives

QSAR and Combinatorial Science

Volumn 28, Issue 4, 2009, Pages 447-457

  Lather, Viney ^a   Fernandes, Miguel X ^a  

^a UNIVERSITY OF MADEIRA   (Portugal)

Author keywords

Artificial neural network (ANN); Indanylacetic acids; Multiple linear regression (MLR); Peroxisome proliferator activated receptor (PPAR); QSAR

Indexed keywords

CELLS; COMPUTATIONAL CHEMISTRY; CYTOLOGY; ELECTRONIC STRUCTURE; LIGANDS; METABOLISM; MOLECULES; NEURAL NETWORKS; STATISTICAL TESTS; TISSUE;

ACID DERIVATIVE; AGONISTIC ACTIVITY; ARTIFICIAL NEURAL NETWORK; DESCRIPTORS; INDANYLACETIC ACID; MULTIPLE LINEAR REGRESSION; MULTIPLE LINEAR REGRESSIONS; PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR; PEROXISOME PROLIFERATOR-ACTIVATED RECEPTOR; QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP;

MULTIPLE LINEAR REGRESSION;

INDANYLACETIC ACID DERIVATIVE; PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR DELTA; PEROXISOME PROLIFERATOR ACTIVATED RECEPTOR DELTA AGONIST; UNCLASSIFIED DRUG;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; CONTROLLED STUDY; DRUG CLASSIFICATION; DRUG DESIGN; DRUG SCREENING; DRUG STRUCTURE; GEOMETRY; MULTIPLE LINEAR REGRESSION ANALYSIS; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RANDOMIZATION; STRUCTURE ANALYSIS;

EID: 66149137609     PISSN: 1611020X     EISSN: 16110218     Source Type: Journal    
DOI: 10.1002/qsar.200810092     Document Type: Article

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