A data mining approach to in vivo classification of psychopharmacological drugs

Neuropsychopharmacology

Volumn 34, Issue 3, 2009, Pages 607-623

  Kafkafi, Neri ^a,c   Yekutieli, Daniel ^b   Elmer, Greg I ^a  

^a UNIVERSITY OF MARYLAND SCHOOL OF MEDICINE   (United States)

^b TEL AVIV UNIVERSITY   (Israel)

^c MARYLAND PSYCHIATRIC RESEARCH CENTER   (United States)

Author keywords

Animal model; Drug discovery; Locomotor behavior; Mouse; Pattern array; SEE

Indexed keywords

CENTRAL STIMULANT AGENT; COCAINE; CODEINE; FENTANYL; KETAMINE; MAZINDOL; METHAMPHETAMINE; METHYLPHENIDATE; MODAFINIL; MORPHINE; OPIATE; OXYCODONE; PHENCYCLIDINE; PSYCHEDELIC AGENT; SALVINORIN A;

ALGORITHM; ANIMAL EXPERIMENT; ARTICLE; BIOINFORMATICS; CONTROLLED STUDY; DOSE RESPONSE; DRUG CLASSIFICATION; HERITABILITY; IN VIVO STUDY; LOCOMOTION; MALE; MOUSE; NONHUMAN; PATTERN ARRAY; PREDICTION; PRIORITY JOURNAL;

ALGORITHMS; ANALGESICS, OPIOID; ANIMALS; CENTRAL NERVOUS SYSTEM STIMULANTS; DOSE-RESPONSE RELATIONSHIP, DRUG; DRUG DISCOVERY; DRUG EVALUATION, PRECLINICAL; HALLUCINOGENS; MALE; MEDICAL INFORMATICS; MICE; MICE, INBRED C57BL; MICE, INBRED STRAINS; MODELS, ANIMAL; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; QUANTITATIVE TRAIT, HERITABLE;

EID: 58149470814     PISSN: 0893133X     EISSN: None     Source Type: Journal    
DOI: 10.1038/npp.2008.103     Document Type: Article

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