An Introduction to Recursive Neural Networks and Kernel Methods for Cheminformatics

Alessio      Micheli; Alessandro      Sperduti; Antonina      Starita

doi:10.2174/138161207780765981

Abstract

The aim of this paper is to introduce the reader to new developments in Neural Networks and Kernel Machines concerning the treatment of structured domains. Specifically, we discuss the research on these relatively new models to introduce a novel and more general approach to QSPR/QSAR analysis. The focus is on the computational side and not on the experimental one.

Keywords: qsar/qspr, recursive neural networks, kernel for structures, kernel methods, learning in structured domains, machine learning

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Current Pharmaceutical Design

Title: An Introduction to Recursive Neural Networks and Kernel Methods for Cheminformatics

Volume: 13 Issue: 14

Author(s): Alessio Micheli, Alessandro Sperduti and Antonina Starita

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Keywords: qsar/qspr, recursive neural networks, kernel for structures, kernel methods, learning in structured domains, machine learning

Abstract: The aim of this paper is to introduce the reader to new developments in Neural Networks and Kernel Machines concerning the treatment of structured domains. Specifically, we discuss the research on these relatively new models to introduce a novel and more general approach to QSPR/QSAR analysis. The focus is on the computational side and not on the experimental one.

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Micheli Alessio, Sperduti Alessandro and Starita Antonina, An Introduction to Recursive Neural Networks and Kernel Methods for Cheminformatics, Current Pharmaceutical Design 2007; 13 (14) . https://dx.doi.org/10.2174/138161207780765981