Universiti Teknologi Malaysia Institutional Repository

High-dimensional QSAR prediction of anticancer potency of imidazo[4,5-b]pyridine derivatives using adjusted adaptive LASSO

Algamal, Zakariya Yahya and Lee, Muhammad Hisyam and Al-Fakih, Abdo Mohammed and Aziz, Madzlan (2015) High-dimensional QSAR prediction of anticancer potency of imidazo[4,5-b]pyridine derivatives using adjusted adaptive LASSO. Journal of Chemometrics, 29 (10). pp. 547-556. ISSN 0886-9383

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1002/cem.2741

Abstract

In high-dimensional quantitative structure-activity relationship (QSAR) studies, identifying relevant molecular descriptors is a major goal. In this study, a proposed penalized method is used as a tool for molecular descriptors selection. The method, called adjusted adaptive least absolute shrinkage and selection operator (LASSO) (AALASSO), is employed to study the high-dimensional QSAR prediction of the anticancer potency of a series of imidazo[4,5-b]pyridine derivatives. This proposed penalized method can perform consistency selection and deal with grouping effects simultaneously. Compared with other commonly used penalized methods, such as LASSO and adaptive LASSO with different initial weights, the results show that AALASSO obtains the best predictive ability not only by consistency selection but also by encouraging grouping effects in selecting more correlated molecular descriptors. Hence, we conclude that AALASSO is a reliable penalized method in the field of high-dimensional QSAR studies

Item Type:Article
Uncontrolled Keywords:anticancer potency, consistency selection, grouping effects
Subjects:Q Science > QA Mathematics
Divisions:Science
ID Code:55579
Deposited By: Fazli Masari
Deposited On:20 Sep 2016 01:21
Last Modified:15 Feb 2017 03:37

Repository Staff Only: item control page