This paper describes the application of the Relaxation By Elimination (RBE) method to matching the 3D structure of molecules in chemical databases within the frame work of binary correlation matrix memories. The paper illustrates that, when combined with distributed representations, the method maps well onto these networks, allowing high performance implementation in parallel systems. It outlines the motivation, the neural architecture, the RBE method and presents some results of matching small molecules against a database of 100,000 models
Unconventional computing paradigms are typically very difficult to program. By implementing efficien...
Many 3D QSAR methods require the alignment of the molecules in a dataset, which can require a fair a...
We present the application of Cascade Correlation for structures to QSPR (quantitative structure-pro...
The recognition of chemical similarities between molecules plays an important role in chemical scie...
Molecular similarity calculations are important for rational drug design. Time constraints prevent t...
Molecular similarity searching is a process to find chemical compounds that are similar to a target ...
This paper discusses algorithmic techniques for measuring the degree of similarity between pairs of ...
Despite its fundamental importance and widespread use for assessing reaction success in organic chem...
High-throughput computational materials design promises to greatly accelerate the process of discove...
Self Organising Map (SOM), also known as Kohonen Neural Network, is tested as a non supervised proce...
The quality of a chemical retrieval system heavily depends on its molecular similarity function whic...
The ensemble of conceivable molecules is referred to as the Chemical Space. In this article we descr...
Graduate School of Artificial Intelligence ArtificiWe present a new way to express the similarity be...
Poster presentation In pharmaceutical research and drug development, machine learning methods play a...
The combination of modern scientific computing with electronic structure theory can lead to an unpre...
Unconventional computing paradigms are typically very difficult to program. By implementing efficien...
Many 3D QSAR methods require the alignment of the molecules in a dataset, which can require a fair a...
We present the application of Cascade Correlation for structures to QSPR (quantitative structure-pro...
The recognition of chemical similarities between molecules plays an important role in chemical scie...
Molecular similarity calculations are important for rational drug design. Time constraints prevent t...
Molecular similarity searching is a process to find chemical compounds that are similar to a target ...
This paper discusses algorithmic techniques for measuring the degree of similarity between pairs of ...
Despite its fundamental importance and widespread use for assessing reaction success in organic chem...
High-throughput computational materials design promises to greatly accelerate the process of discove...
Self Organising Map (SOM), also known as Kohonen Neural Network, is tested as a non supervised proce...
The quality of a chemical retrieval system heavily depends on its molecular similarity function whic...
The ensemble of conceivable molecules is referred to as the Chemical Space. In this article we descr...
Graduate School of Artificial Intelligence ArtificiWe present a new way to express the similarity be...
Poster presentation In pharmaceutical research and drug development, machine learning methods play a...
The combination of modern scientific computing with electronic structure theory can lead to an unpre...
Unconventional computing paradigms are typically very difficult to program. By implementing efficien...
Many 3D QSAR methods require the alignment of the molecules in a dataset, which can require a fair a...
We present the application of Cascade Correlation for structures to QSPR (quantitative structure-pro...