Use of Entropy and Shrinkage method for Gene Expression Data Analysis

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F14%3A10287814" target="_blank" >RIV/00216208:11110/14:10287814 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Use of Entropy and Shrinkage method for Gene Expression Data Analysis
Original language description
The aim of my research is the identification of new approaches for dimension reduction and classification of high dimensional gene expression data. The problem of dimensionality reduction means reducing the large number of genes only on the important genes which are somehow bundled together. The problem of classification means finding few genes from a large number of genes which are important for the classification of an uknown sample to a certain group (such as disease). I would like to establish bothtasks, i.e. dimension reduction and classification, on methods of information theory. The most known variables in information theory are Shannon entropy or mutual information. I would like to combine methods of information theory with the shrinkage method which is a generalization of the concept of the James-Stein estimate.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)