Advanced Techniques in Biology & Medicine
Open Access

Fatima Adilova

Publications

• Research Article
  Data Set Analysis for the Calculation of the QSAR Models Predictive Efficiency Based on Activity Cliffs
  Author(s): Fatima Adilova and Alisher Ikramov Fatima Adilova and Alisher Ikramov
  
  The activity cliff concept is of high relevance for medicinal chemistry. Herein, we explore a concept of “data set modelability”, i.e., a priori estimate of the feasibility to obtain externally predictive QSAR models for a data set of bioactive compounds. This concept has emerged from analyzing the effect of so-called “activity cliffs” on the overall performance of QSAR models. Some indexes of “modelability” (SALI, ISAC, and MODI) are known already. We extended the version of MODI to data sets of compounds with real activity values. The predictive efficiency of QSAR models is expressed as the correct classification rate by SVM algorithm, which compared with the results of the other two algorithms: algorithm MODI and Voronin’s algorithm modified by the authors. Comparative analysis of the results performed using Pearson’s correlation coef.. View More»
  DOI: 10.4172/2379-1764.1000216

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