title: A Novel Strategy of Structural Similarity Based Consensus Modeling.
abstract: A novel strategy of "structural similarity based consensus modeling" (SSCM) based on "model distance and guided model selection" (MD-QGMS) submodel set was proposed. The SSCM strategy is built upon a hypothesis, that is, similar compounds are most probably predicted more accurately by a same submodel among a model population, which can be concluded from the fact that models employing a different set of descriptors can predict compounds with specific structures more accurately. It is proved that the proposed SSCM strategy can remarkably improve the external prediction ability of QSAR models by employing two different datasets. In future, the proposed SSCM strategy may provide a new direction to develop more accurate predictive models.
authors.affiliation: College of Life Sciences, Northwest A & F University, Yangling 712100, 22 Xinong Road, P. R. China tel: +86-029-87092262. leibl@nwsuaf.edu.cn.
authors.forename: Beilei
authors.initials: B
authors.lastname: Lei
authors.affiliation: School of Pharmacy, Lanzhou University, Lanzhou 730000, P. R. China.
authors.forename: Jiazhong
authors.initials: J
authors.lastname: Li
authors.affiliation: State Key Laboratory of Applied Organic Chemistry, Department of Chemistry, Lanzhou University, Lanzhou 730000, P. R. China.
authors.forename: Xiaojun
authors.initials: X
authors.lastname: Yao
keywords: Average consensus modeling; Genetic algorithm; Model distance and Q2LOO guided model selection; Structural similarity based consensus modeling