Semi-automatic mining of correlated data from a complex database: Correlation network visualization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00092617" target="_blank" >RIV/00216224:14330/16:00092617 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7802783/" target="_blank" >http://ieeexplore.ieee.org/document/7802783/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCABS.2016.7802783" target="_blank" >10.1109/ICCABS.2016.7802783</a>
Alternative languages
Result language
angličtina
Original language name
Semi-automatic mining of correlated data from a complex database: Correlation network visualization
Original language description
In previous work we have addressed the issue of frequent ad-hoc queries in deeply-structured databases. We wrote a library of functions AutodenormLib.py for issuing proper JOIN commands to denormalize an arbitrary subset of stored data for downstream processing. This may include statistical analysis, visualization or machine learning. Here, we visualize the content of the Thalamoss biomedical database as a correlation network. The network is created by calculating pairwise correlations through all pairs of variables, whether they be numerical, ordinal or nominal. We subsequently construct the network over the entire set of variables, clustering variables with similar effects to discover group relationships between the various biomedical characteristics. We use a semi-automatic procedure that makes the selection of all pairs possible and discuss issues of dealing with different types of variables.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/7E13011" target="_blank" >7E13011: THALAssaemia MOdular Stratification System for personalized therapy of beta-thalassemia</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computational Advances in Bio and Medical Sciences (ICCABS), 2016 IEEE 6th International Conference on
ISBN
9781509041992
ISSN
2473-4659
e-ISSN
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Number of pages
2
Pages from-to
1-2
Publisher name
IEEE
Place of publication
New York
Event location
Atlanta, GA, USA
Event date
Oct 13, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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