Use of Entropy and Shrinkage method for Gene Expression Data Analysis

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Use of Entropy and Shrinkage method for Gene Expression Data Analysis

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Use of Entropy and Shrinkage method for Gene Expression Data Analysis

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal on Biomedicine and Healthcare

ISSN

1805-8698

e-ISSN

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Svazek periodika

2

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

3

Strana od-do

6-8

Kód UT WoS článku

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EID výsledku v databázi Scopus

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