Network-Constrained Forest for Regularized Omics Data Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00221458" target="_blank" >RIV/68407700:21230/14:00221458 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/BIBM.2014.6999193" target="_blank" >http://dx.doi.org/10.1109/BIBM.2014.6999193</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/BIBM.2014.6999193" target="_blank" >10.1109/BIBM.2014.6999193</a>
Alternative languages
Result language
angličtina
Original language name
Network-Constrained Forest for Regularized Omics Data Classification
Original language description
Contemporary molecular biology deals with a wide and heterogeneous set of measurements to model and understand underlying biological processes including complex diseases. Machine learning provides a frequent approach to build such models. However, the models built solely from measured data often suffer from overfitting, as the sample size is typically much smaller than the number of measured features. In this paper, we propose a random forest-based classifier that minimizes this overfitting with the aidof prior knowledge in the form of a feature interaction network. We illustrate the proposed method in the task of disease classification based on measured mRNA and miRNA profiles complemented by the interaction network composed of the miRNA-mRNA targetrelations and mRNA-mRNA interactions corresponding to the interactions between their encoded proteins. We demonstrate that the proposed network-constrained forest employs prior knowledge to increase learning bias and consequently to impro
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
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
Proceedings 2014 IEEE International Conference on Bioinformatics and Biomedicine
ISBN
978-1-4799-5668-5
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
410-417
Publisher name
IEEE
Place of publication
Piscataway
Event location
Belfast
Event date
Nov 2, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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