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Prediction of Molecular Properties by Recursive Neural Networks: Application to the glass transition temperature of acrylic polymers - Softcover

Bertinetto, Carlo Giuseppe; Duce, Celia; Solaro, Roberto

 
9783639162097: Prediction of Molecular Properties by Recursive Neural Networks: Application to the glass transition temperature of acrylic polymers
Softcover
ISBN 10: 3639162099 ISBN 13: 9783639162097
Verlag: VDM Verlag Dr. Müller, 2010

Inhaltsangabe

In the past few years, a novel approach in cheminformatics for the Quantitative Structure-Property Relationship (QSPR) analysis of physical, chemical and biological properties of chemical compounds was developed at the University of Pisa. This methodology is based on the direct treatment of molecular structure, without using numerical descriptors, and employs recursive neural networks. In subsequent studies it was successfully used to predict various properties of different classes of compounds. It is a promising tool in the evaluation of existing substances, as well as in the design of new materials. This master thesis focuses on the prediction of the properties of polymers, a problem not easily treatable with traditional methods based on molecular descriptors. The study explores different representational issues and show the accuracy and flexibility of the structure-based QSPR approach.

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Verlag
VDM Verlag Dr. Müller
Erscheinungsdatum
2010
Sprache
Englisch
ISBN 10 
3639162099
ISBN 13 
9783639162097
Einband
Taschenbuch
Anzahl der Seiten
116
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Zeitfracht Medien GmbH
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