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Distribution of QSARs correlation coefficients

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CONTRIBUTORS:
  Author Lorentz JANTSCHI (Technical University of Cluj-Napoca)
  Author Sorana D. BOLBOACA (Iuliu Hatieganu University of Medicine and Pharmacy Cluj-Napoca)
  Author Mircea V. DIUDEA
  Author Radu E. SESTRAS (University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania)
PROCEEDINGS TITLE:
  Visualization and Modeling in Chemistry
YEAR: 2010
PUB TYPE: Conference Paper in Proceedings
PAGES: 13 - 14
SUBJECT(S): mathematics - statistics; mathematics - modeling; chemistry - computational; chemistry - organic; biology - bioinformatics
DISCIPLINE: Chemistry
HTTP: http://lori.academicdirect.org/works/?f=254
LANGUAGE: English
PUB ID: 103-483-644 (Last edited on 2011/01/17 06:47:06 US/Mountain)
SPONSOR(S):
 
ABSTRACT:
For set of ordnance compounds, with size ranging from 5 (one case) to 8 (11 cases) were previously studied the effect in the aquatic environment (on the marine life). For a number of 24 biological activities at which a computed property were added (OPLS-SAE) were created the pool of simple linear regressions relating the activities with the structure by using the MDFV methodology (implies creating the pool of descriptors and applying of adaptation criteria to the descriptors). From the pool of simple linear regressions were selected the ones being statistically significant (probability to reject the linear model less or equal to 0.05). A study regarding the distribution of the correlation coefficients for the selected simple linear regressions was conducted. Three distribution laws were proved to be relevant for the population of correlation coefficients (Beta, Generalized Pareto and Pert). For these three distributions a further study were conducted regarding the classification of the activities into one or another distribution. The study shown that the Chi-Square statistic was the best classifier of the activities: only one disagreement with the true positive classification simultaneous independent events of all three. The outcome of the study is that 48% of the correlation coefficients populations of significant simple linear regressions are Beta distributed, 40% are Generalized Pareto, and the rest - 12% - including the OPLS-SAE, are Pert distributed.
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