LogP is becoming a practical parallel computation model that meets the demanding of parallel computersand parallel algorithms. So it is important to re-design parallel algorithms on the LogP model. This paper studies ...LogP is becoming a practical parallel computation model that meets the demanding of parallel computersand parallel algorithms. So it is important to re-design parallel algorithms on the LogP model. This paper studies theparallel algorithm of computing converse matrix on the simplified LogP model, and gets the simulating results.展开更多
New descriptors were constructed and structures of some oxygen-containing organic compounds were parameterized. The multiple linear regression（MLR） and partial least squares regression（PLS） methods were employed t...New descriptors were constructed and structures of some oxygen-containing organic compounds were parameterized. The multiple linear regression（MLR） and partial least squares regression（PLS） methods were employed to build two relationship models between the structures and octanol/water partition coefficients（LogP） of the compounds. The modeling correlation coefficients（R） were 0.976 and 0.922, and the ＂leave one out＂ cross validation correlation coefficients（R（CV）） were 0.973 and 0.909, respectively. The results showed that the structural descriptors could well characterize the molecular structures of the compounds; the stability and predictive power of the models were good.展开更多
文摘LogP is becoming a practical parallel computation model that meets the demanding of parallel computersand parallel algorithms. So it is important to re-design parallel algorithms on the LogP model. This paper studies theparallel algorithm of computing converse matrix on the simplified LogP model, and gets the simulating results.
基金supported by the Youth Foundation of Education Bureau,Sichuan Province(13ZB0003)
文摘New descriptors were constructed and structures of some oxygen-containing organic compounds were parameterized. The multiple linear regression（MLR） and partial least squares regression（PLS） methods were employed to build two relationship models between the structures and octanol/water partition coefficients（LogP） of the compounds. The modeling correlation coefficients（R） were 0.976 and 0.922, and the ＂leave one out＂ cross validation correlation coefficients（R（CV）） were 0.973 and 0.909, respectively. The results showed that the structural descriptors could well characterize the molecular structures of the compounds; the stability and predictive power of the models were good.
