Relational Subgroup Discovery for Gene Expression Data Mining

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F05%3A03115158" target="_blank" >RIV/68407700:21230/05:03115158 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Relational Subgroup Discovery for Gene Expression Data Mining

Original language description

We propose a methodology for predictive classification from gene expression data, able to combine the robustness of high-dimensional statistical classification methods with the comprehensibility and interpretability of simple logic-based models. We firstconstruct a robust classifier combining contributions of a large number of gene expression values, and then search for compact summarizations of subgroups among genes associated in the classifier with a given class. The subgroups are described by meansof relational logic features extracted from publicly available gene annotations. The curse of dimensionality pertaining to the gene expression based classification problem due to the large number of attributes (genes) is turned into an advantage in the secondary subgroup discovery task, as here the original attributes become learning examples.

Czech name

Není k dispozici

Czech description

Není k dispozici

Type

A - Audiovisual production

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2005

Confidentiality

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

ISBN

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Place of publication

Praha

Publisher/client name

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Version

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Carrier ID

neuvedeno