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Multiblock Discriminant Analysis for Integrative Genomic Study
Joint Authors
Kang, Mingon
Kim, Dong-Chul
Gao, Jean X.
Liu, Chunyu
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-17
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Human diseases are abnormal medical conditions in which multiple biological components are complicatedly involved.
Nevertheless, most contributions of research have been made with a single type of genetic data such as Single Nucleotide Polymorphism (SNP) or Copy Number Variation (CNV).
Furthermore, epigenetic modifications and transcriptional regulations have to be considered to fully exploit the knowledge of the complex human diseases as well as the genomic variants.
We call the collection of the multiple heterogeneous data “multiblock data.” In this paper, we propose a novel Multiblock Discriminant Analysis (MultiDA) method that provides a new integrative genomic model for the multiblock analysis and an efficient algorithm for discriminant analysis.
The integrative genomic model is built by exploiting the representative genomic data including SNP, CNV, DNA methylation, and gene expression.
The efficient algorithm for the discriminant analysis identifies discriminative factors of the multiblock data.
The discriminant analysis is essential to discover biomarkers in computational biology.
The performance of the proposed MultiDA was assessed by intensive simulation experiments, where the outstanding performance comparing the related methods was reported.
As a target application, we applied MultiDA to human brain data of psychiatric disorders.
The findings and gene regulatory network derived from the experiment are discussed.
American Psychological Association (APA)
Kang, Mingon& Kim, Dong-Chul& Liu, Chunyu& Gao, Jean X.. 2015. Multiblock Discriminant Analysis for Integrative Genomic Study. BioMed Research International،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1056708
Modern Language Association (MLA)
Kang, Mingon…[et al.]. Multiblock Discriminant Analysis for Integrative Genomic Study. BioMed Research International No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1056708
American Medical Association (AMA)
Kang, Mingon& Kim, Dong-Chul& Liu, Chunyu& Gao, Jean X.. Multiblock Discriminant Analysis for Integrative Genomic Study. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1056708
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1056708