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ENGL
2008

Improving the Development of QSAR Prediction Models with the use of Approximate Similarity Approach

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Improving the Development of QSAR Prediction Models with the use of Approximate Similarity Approach
The improvement on the QSAR prediction of the trans-stilbenes affinity for the -amyloid peptide (employed for detecting the Alzheimer disease) achieved by means of using approximate similarity measurement is presented in this work. A wide spectrum of similarity methods is described, and results obtained by approximate similarity are compared with those obtained by constitutional, fingerprint and descriptor-based similarity. The fact of using similarity corrections by considering distances between the non-isomorphic fragments (the approximate similarity concept) led to accurate QSAR models (Q2 > 0.80). The high predictive ability achieved by simple methods is remarked.
Irene Luque Ruiz, Manuel Urbano-Cuadrado, Miguel &
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where ENGL
Authors Irene Luque Ruiz, Manuel Urbano-Cuadrado, Miguel Ángel Gómez-Nieto
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