Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites
We show how transformation group ideas can be naturally used to generate efficient algorithms for scientific computations. The general approach is illustrated on the example of determining, from the experimental data, the dissociation constants related to multiple binding sites. We also explain how...
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Online Access: | http://www.mdpi.com/2073-8994/6/1/90 |
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doaj-bd3fee63268d4d91bd1f0e73f6cbb34d2020-11-25T01:05:13ZengMDPI AGSymmetry2073-89942014-02-01619010210.3390/sym6010090sym6010090Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding SitesAndres Ortiz0Vladik Kreinovich1Department of Mathematical Sciences, University of Texas at El Paso, 500 W. University, El Paso, TX 79968, USADepartment of Computer Science, University of Texas at El Paso, 500 W. University, El Paso, TX 79968, USAWe show how transformation group ideas can be naturally used to generate efficient algorithms for scientific computations. The general approach is illustrated on the example of determining, from the experimental data, the dissociation constants related to multiple binding sites. We also explain how the general transformation group approach is related to the standard (backpropagation) neural networks; this relation justifies the potential universal applicability of the group-related approach.http://www.mdpi.com/2073-8994/6/1/90symmetriestransformation group approachmultiple binding sitesneural networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Andres Ortiz Vladik Kreinovich |
spellingShingle |
Andres Ortiz Vladik Kreinovich Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites Symmetry symmetries transformation group approach multiple binding sites neural networks |
author_facet |
Andres Ortiz Vladik Kreinovich |
author_sort |
Andres Ortiz |
title |
Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites |
title_short |
Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites |
title_full |
Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites |
title_fullStr |
Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites |
title_full_unstemmed |
Using Symmetries (Beyond Geometric Symmetries) in Chemical Computations: Computing Parameters of Multiple Binding Sites |
title_sort |
using symmetries (beyond geometric symmetries) in chemical computations: computing parameters of multiple binding sites |
publisher |
MDPI AG |
series |
Symmetry |
issn |
2073-8994 |
publishDate |
2014-02-01 |
description |
We show how transformation group ideas can be naturally used to generate efficient algorithms for scientific computations. The general approach is illustrated on the example of determining, from the experimental data, the dissociation constants related to multiple binding sites. We also explain how the general transformation group approach is related to the standard (backpropagation) neural networks; this relation justifies the potential universal applicability of the group-related approach. |
topic |
symmetries transformation group approach multiple binding sites neural networks |
url |
http://www.mdpi.com/2073-8994/6/1/90 |
work_keys_str_mv |
AT andresortiz usingsymmetriesbeyondgeometricsymmetriesinchemicalcomputationscomputingparametersofmultiplebindingsites AT vladikkreinovich usingsymmetriesbeyondgeometricsymmetriesinchemicalcomputationscomputingparametersofmultiplebindingsites |
_version_ |
1725195604227784704 |