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Authors: Jiří Kléma 1 ; Jan Zahálka 1 ; Michael Anděl 1 and Zdeněk Krejčík 2

Affiliations: 1 Czech Technical University, Czech Republic ; 2 Institute of Hematology and Blood Transfusion, Czech Republic

Keyword(s): Gene Expression, Machine Learning, microRNA, Classification, Prior Knowledge, Myelodysplastic Syndrome.

Related Ontology Subjects/Areas/Topics: Bioinformatics ; Biomedical Engineering ; Data Mining and Machine Learning ; Genomics and Proteomics ; Pattern Recognition, Clustering and Classification

Abstract: The goal of our work is to integrate conventional mRNA expression profiles with miRNA expressions using the knowledge of their validated or predicted interactions in order to improve class prediction in genetically determined diseases. The raw mRNA and miRNA expression features become enriched or replaced by new aggregated features that model the mRNA-miRNA interaction. The proposed subtractive integration method is directly motivated by the inhibition/degradation models of gene expression regulation. The method aggregates mRNA and miRNA expressions by subtracting a proportion of miRNA expression values from their respective target mRNAs. The method is used to model the outcome or development of myelodysplastic syndrome, a blood cell production disease often progressing to leukemia. The reached results demonstrate that the integration improves classification performance when dealing with mRNA and miRNA profiles of comparable predictive power.

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Paper citation in several formats:
Kléma, J.; Zahálka, J.; Anděl, M. and Krejčík, Z. (2014). Knowledge-based Subtractive Integration of mRNA and miRNA Expression Profiles to Differentiate Myelodysplastic Syndrome. In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2014) - BIOINFORMATICS; ISBN 978-989-758-012-3; ISSN 2184-4305, SciTePress, pages 31-39. DOI: 10.5220/0004752200310039

@conference{bioinformatics14,
author={Ji\v{r}í Kléma. and Jan Zahálka. and Michael Anděl. and Zdeněk Krejčík.},
title={Knowledge-based Subtractive Integration of mRNA and miRNA Expression Profiles to Differentiate Myelodysplastic Syndrome},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2014) - BIOINFORMATICS},
year={2014},
pages={31-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004752200310039},
isbn={978-989-758-012-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2014) - BIOINFORMATICS
TI - Knowledge-based Subtractive Integration of mRNA and miRNA Expression Profiles to Differentiate Myelodysplastic Syndrome
SN - 978-989-758-012-3
IS - 2184-4305
AU - Kléma, J.
AU - Zahálka, J.
AU - Anděl, M.
AU - Krejčík, Z.
PY - 2014
SP - 31
EP - 39
DO - 10.5220/0004752200310039
PB - SciTePress

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