Gene Ontology Driven Feature Filtering from Microarray Data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F10%3APU86238" target="_blank" >RIV/00216305:26230/10:PU86238 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

čeština

Original language name

Gene Ontology Driven Feature Filtering from Microarray Data

Original language description

Microarray data is high-dimensional and noisy. Dimension reduction, i.e. selecting a small number of genes, is an effective way to improve mining efficiency. We propose a novel approach that integrates gene ontology knowledge at the level of feature selection into microarray data to improve binary class prediction. The advantage of this filtering approach lies in considering gene-to-gene relations and selecting more meaningful features comparing to the methods evaluating genes in isolation. In addition,gene ontology knowledge can overcome the limitations of noisy microarray data. Our approach is evaluated on a real benchmark dataset.

Czech name

Gene Ontology Driven Feature Filtering from Microarray Data

Czech description

Microarray data is high-dimensional and noisy. Dimension reduction, i.e. selecting a small number of genes, is an effective way to improve mining efficiency. We propose a novel approach that integrates gene ontology knowledge at the level of feature selection into microarray data to improve binary class prediction. The advantage of this filtering approach lies in considering gene-to-gene relations and selecting more meaningful features comparing to the methods evaluating genes in isolation. In addition,gene ontology knowledge can overcome the limitations of noisy microarray data. Our approach is evaluated on a real benchmark dataset.

Type

D - Article in proceedings

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

<a href="/en/project/2B06052" target="_blank" >2B06052: Determination of markers, screening and early diagnostics of cancer diseases using highly automated processing of multidimensional biomedical images</a><br>

Continuities

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

Publication year

2010

Confidentiality

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

Article name in the collection

Znalosti 2010

ISBN

978-80-245-1636-3

ISSN

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e-ISSN

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Number of pages

4

Pages from-to

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Publisher name

NEUVEDEN

Place of publication

Jindřichův Hradec

Event location

Jindřichův Hradec

Event date

Feb 3, 2010

Type of event by nationality

CST - Celostátní akce

UT code for WoS article

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