current mathematical methods used in qsarqspr studies当前数学方法用于qsarqspr研究.pdf

Int. J. Mol. Sci. 2009, 10, 1978-1998; doi:10.3390/ijm OPEN ACCESS International Journal of Molecular Sciences ISSN 1422-0067 /journal/ijms Review Current Mathematical Methods Used in QSAR/QSPR Studies # # Peixun Liu and Wei Long Institute of Radiation Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences, Tianjin 300192, P.R. China; E-Mails: longwaylong@ (W.L.); pharm8888@ (P.-X.L.); Tel. +86-22 Fax: +86-22 # These authors contributed equally to this work Received: 19 March 2009 / Accepted: 28 April 2009 / Published: 29 April 2009 Abstract: This paper gives an overview of the mathematical methods currently used in quantitative structure-activity/property relationship (QASR/QSPR) studies. Recently, the mathematical methods applied to the regression of QASR/QSPR models are developing very fast, and new methods, such as Gene Expression Programming (GEP), Project Pursuit Regression (PPR) and Local Lazy Regression (LLR) have appeared on the QASR/QSPR stage. At the same time, the earlier methods, including Multiple Linear Regression (MLR), Partial Least Squares (PLS), Neural Networks (NN), Support Vector Machine (SVM) and so on, are being upgraded to improve their performance in QASR/QSPR studies. These new and upgraded methods and algorithms are described in detail,