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                    COMPARISON OF SEVERAL REGRESSION METHODS APPLIED IN DISPERSE DYE-CELLULOSE BINDING
                
                                    
                
                
                    Published:
01 November 2009
by MDPI
in The 13th International Electronic Conference on Synthetic Organic Chemistry
session Computational Chemistry
                
                                    
                
                
                    Abstract: Quantitative structure-affinity relationships were applied to a series of 27 disperse dyes by partial least squares (PLS) analysis and compared to previously published MLR (multiple linear regression), MTD (minimum steric difference) and CoMFA (comparative molecular field analysis) results. Calculated 0D, 1D and 2D structural dye features were correlated to their affinity for cellulose by PLS. A robust model (R2X(cum) = 0.617, R2Y(cum) = 0.959, Q2(cum) = 0.953) with predictive power was obtained from these correlations. Better statistical results were achieved in the PLS model, in comparison to the previous MLR, MTD and CoMFA results, but the three-dimensional models obtained by CoMFA gave more information on the dye-cellulose specific interactions.
                
                
                
                
                 
            
 
        
    
    
         
    
    
         
    
    
         
    
    
         
    
 
                                