2019
DOI: 10.1007/s00044-019-02455-w
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Identification of prodigious and under-privileged structural features for RG7834 analogs as Hepatitis B virus expression inhibitor

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Cited by 4 publications
(3 citation statements)
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“…To test the multicollinearity of the descriptors involved in the model and avoid “apparent” prediction, a power matrix of correlation (1) was generated. Low collinearity was confirmed by the values of the correlation coefficient ( R ≤ 0.7) and verified with the value of the multivariate correlation index ( Kxx ) and the difference between global correlation among descriptors (Δ K ≥ 0.05) [ 37 , 40 ] ( Table 4 and Table 5 ). The stability and robustness of a model were confirmed by parameters of internal validation employing leave-one-out (LOO) cross-validation.…”
Section: Resultsmentioning
confidence: 63%
See 1 more Smart Citation
“…To test the multicollinearity of the descriptors involved in the model and avoid “apparent” prediction, a power matrix of correlation (1) was generated. Low collinearity was confirmed by the values of the correlation coefficient ( R ≤ 0.7) and verified with the value of the multivariate correlation index ( Kxx ) and the difference between global correlation among descriptors (Δ K ≥ 0.05) [ 37 , 40 ] ( Table 4 and Table 5 ). The stability and robustness of a model were confirmed by parameters of internal validation employing leave-one-out (LOO) cross-validation.…”
Section: Resultsmentioning
confidence: 63%
“…The obtained model satisfied the suggested threshold values of fitting criteria: coefficient of determination ( R 2 tr ) greater than 0.60, as well as higher or equal to the adjusted coefficient of determination ( R 2 adj ). Also, the concordance correlation coefficient of the training set ( CCC tr ) is higher than 0.80 [ 37 , 38 , 39 ]. To test the multicollinearity of the descriptors involved in the model and avoid “apparent” prediction, a power matrix of correlation (1) was generated.…”
Section: Resultsmentioning
confidence: 99%
“…The model demonstrates a satisfactory stability in internal validation ( Q 2 LOO ≥ 0.5; Q 2 LMO ≥ 0.6; RMSE tr < RMSE cv ; r 2 m ≥ 0.6) ( Kiralj and Ferreira, 2009 ; Veerasamy et al, 2011 ). Parameters of Y-scrambling ( R 2 Yscr < 0.2; Q 2 Yscr < 0.2) highlight that the model is robust and not obtained by chance correlation ( Masand et al, 2019 ). The only failed parameter is the concordance correlation coefficient obtained by cross-validation ( CCC cv ) that is higher than 0.85.…”
Section: Resultsmentioning
confidence: 99%