Comparative study to predict toxic modes of action of phenols from molecular structures

SAR and QSAR in Environmental Research

Volumn 24, Issue 3, 2013, Pages 235-251

  Brito Sanchez Y ^a,b   Castillo Garit, J A ^a,c   Le Thi Thu, H ^a   Gonzalez Madariaga Y ^b   Torrens, F ^c   Marrero Ponce, Y ^a,c   Rodriguez Borges J E ^d  

^a CENTRAL UNIVERSITY OF LAS VILLAS   (Cuba)

^b Medical Sciences University   (Cuba)

^c UNIVERSITY OF VALENCIA   (Spain)

^d UNIVERSITY OF PORTO   (Portugal)

Author keywords

atom based quadratic indices; machine learning technique; mode of toxic action; phenol derivative; quantitative structure toxicity relationship

Indexed keywords

DISCRIMINANT ANALYSIS; LEARNING ALGORITHMS; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

ATOM-BASED QUADRATIC INDEX; COMPARATIVES STUDIES; ELECTROPHILES; MACHINE LEARNING TECHNIQUES; MODE OF TOXIC ACTIONS; PHENOL DERIVATIVES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP MODELING; QUANTITATIVE STRUCTURE-TOXICITY RELATIONSHIP; QUANTITATIVE STRUCTURES; TOXIC MODE OF ACTION;

PHENOLS;

MYXOZOA; PROTOZOA; TETRAHYMENA PYRIFORMIS;

EID: 84875227923     PISSN: 1062936X     EISSN: 1029046X     Source Type: Journal    
DOI: 10.1080/1062936X.2013.766260     Document Type: Article

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