Document Detail

Neural networks evaluating NMR data: an approach to visualize similarities and relationships of sol-gel derived inorganic-organic and organometallic hybrid polymers.
MedLine Citation:
PMID:  11855964     Owner:  NLM     Status:  PubMed-not-MEDLINE    
An artificial neural network (ANN)--the Kohonen Self-Organizing Feature Map (SOM)-is used to evaluate solid-state NMR spectroscopic derived data of 72 siloxane-based phosphine and organometallic functionalized hybrid polymers. The data set consists of parameters that describe their structural features and their dynamic behavior. The ANN visualizes similarities of the investigated compounds by reducing the dimension of the data set. This allows a comparison of these polymers that was not possible beforehand because of their structural diversity.
Frank Hoehn; Ekkehard Lindner; Hermann A Mayer; Thomas Hermle; Wolfgang Rosenstiel
Related Documents :
15819944 - A neural network model for predicting aquifer water level elevations.
14606364 - Combining artificial neural networks and transrectal ultrasound in the diagnosis of pro...
11038114 - Modelling of the solvent evaporation method for the preparation of controlled release a...
16397774 - Artificial neural networks for assessing the risk of urinary calcium stone among men.
22365644 - A mixture model to correct misclassification of gestational age.
19000644 - Development of comfa and comsia models of cytotoxicity data of anti-hiv-1-phenylamino-1...
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of chemical information and computer sciences     Volume:  42     ISSN:  0095-2338     ISO Abbreviation:  J Chem Inf Comput Sci     Publication Date:    2002 Jan-Feb
Date Detail:
Created Date:  2002-02-21     Completed Date:  2002-04-08     Revised Date:  2003-11-03    
Medline Journal Info:
Nlm Unique ID:  7505012     Medline TA:  J Chem Inf Comput Sci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  36-45     Citation Subset:  -    
Institut für Anorganische Chemie der Universität Tübingen.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Previous Document:  An alignment-independent versatile structure descriptor for QSAR and QSPR based on the distribution ...
Next Document:  Enhanced CACTVS browser of the Open NCI Database.