miXGENE tool for learning from heterogeneous gene expression data using prior knowledge
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00218532" target="_blank" >RIV/68407700:21230/14:00218532 - isvavai.cz</a>
Result on the web
<a href="http://mixgene.felk.cvut.cz/" target="_blank" >http://mixgene.felk.cvut.cz/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CBMS.2014.8" target="_blank" >10.1109/CBMS.2014.8</a>
Alternative languages
Result language
angličtina
Original language name
miXGENE tool for learning from heterogeneous gene expression data using prior knowledge
Original language description
High-throughput genomic technologies have proved to be useful in the search for both genetic disease markers and more complex predictive and descriptive models. By the same token, it became obvious that accurate and interpretable models need to concern more than raw measurements taken at a single phase of gene expression. In order to reach a deeper understanding of the molecular nature of complexly orchestrated biological processes, all the available measurements and existing genomic knowledge need to be fused. In this paper, we introduce a tool for machine learning from heterogeneous gene expression data using prior knowledge. The tool is called miXGENE, it is elaborated upon in close connection with the biological departments that dispose of the above-mentioned data and have a strong interest in their integration within particular problem-oriented projects. The main idea is not merely to capture the transcriptional phase of gene expression quantified by the amount of messenger RNA~(m
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/NT14539" target="_blank" >NT14539: XGENE.ORG -- a public tool for integrated analysis of microarray, microRNA and methylation data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2014 IEEE 27th International Symposium on Computer-Based Medical Systems
ISBN
978-1-4799-4435-4
ISSN
1063-7125
e-ISSN
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Number of pages
4
Pages from-to
247-250
Publisher name
IEEE
Place of publication
Piscataway
Event location
New York
Event date
May 27, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000345222200049