Prediction of Molecular Properties by Recursive Neural Networks di Carlo Giuseppe Bertinetto, Celia Duce, Roberto Solaro edito da VDM Verlag
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Prediction of Molecular Properties by Recursive Neural Networks

Application to the glass transition temperature of acrylic polymers

Editore:

VDM Verlag

EAN:

9783639162097

ISBN:

3639162099

Pagine:
116
Formato:
Paperback
Lingua:
Tedesco
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Descrizione Prediction of Molecular Properties by Recursive Neural Networks

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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