The OECD Principles for (Q)SAR Models in the Context of Knowledge Discovery in Databases (KDD)

Autor: Gabriela, Gómez-Jiménez, Karla, Gonzalez-Ponce, Durbis J, Castillo-Pazos, Abraham, Madariaga-Mazon, Joaquin, Barroso-Flores, Fernando, Cortes-Guzman, Karina, Martinez-Mayorga
Rok vydání: 2018
Předmět:
Zdroj: Advances in protein chemistry and structural biology. 113
ISSN: 1876-1631
Popis: The steps followed in the knowledge discovery in databases (KDD) process are well documented and are widely used in different areas where exploration of data is used for decision making. In turn, while different workflows for developing quantitative structure-activity relationship (QSAR) models have been proposed, including combinatorial use of QSAR, there is now agreement on common requirements for building trustable predictive models. In this work, we analyze and confront the steps involved in KDD and QSAR and present how they comply with the OECD principles for the validation, for regulatory purposes, of QSAR models.
Databáze: OpenAIRE