https://scholars.lib.ntu.edu.tw/handle/123456789/117633
標題: | GEMPLS: A New QSAR Method Combining Generic Evolutionary Method and Partial Least Squares | 作者: | Hutchison, David Kanade, Takeo Kittler, Josef Kleinberg, Jon M. Mattern, Friedemann Mitchell, John C. Naor, Moni Nierstrasz, Oscar Rangan, C. Pandu Steffen, Bernhard Sudan, Madhu Terzopoulos, Demetri Tygar, Dough Vardi, Moshe Y. Weikum, Gerhard |
公開日期: | 2005 | 起(迄)頁: | 125-135 | 來源出版物: | Applications of Evolutionary Computing (Lecture Notes in Computer Science) | 摘要: | We have proposed a new method for quantitative structure-activity relationship (QSAR) analysis. This tool, termed GEMPLS, combines a genetic evolutionary method with partial least squares (PLS). We designed a new genetic operator and used Mahalanobis distance to improve predicted accuracy and speed up a solution for QSAR. The number of latent variables (lv) was encoded into the chromosome of GA, instead of scanning the best lv for PLS. We applied GEMPLS on a comparative binding energy (COMBINE) analysis system of 48 inhibitors of the HIV-1 protease. Using GEMPLS, the cross-validated correlation coefficient (q2) is 0.9053 and external SDEP (SDEPex) is 0.61. The results indicate that GEMPLS is very comparative to GAPLS and GEMPLS is faster than GAPLS for this data set. GEMPLS yielded the QSAR models, in which selected residues are consistent with some experimental evidences. ? Springer-Verlag Berlin Heidelberg 2005. |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/154593 | DOI: | 10.1007/978-3-540-32003-6_13 | SDG/關鍵字: | Binding energy; Enzyme inhibition; Enzymes; Evolutionary algorithms; Genes; Mathematical models; Mathematical operators; Genetic evolutionary method; Genetic operator; Latent variables (lv); Partial least squares (PLS); Genetic engineering |
顯示於: | 資訊工程學系 |
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