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2015 International Conference on Big Data and Smart Computing (BigComp) (2015)
Jeju, South Korea
Feb. 9, 2015 to Feb. 11, 2015
ISBN: 978-1-4799-7303-3
pp: 266-270
Jaya Thomas , Department of Computer Science, State University of New York, Korea, Incheon 406-840, Korea
Lee Sael , Department of Computer Science, State University of New York, Korea, Incheon 406-840, Korea
ABSTRACT
In the big data era, data are not only generated in massive quantity but also in diversity. The heterogeneous characteristics of the diverse data sources on a subject provide complimentary information. However, they pose challenges in data analysis process. Then, what are the existing methods for utilizing theses heterogeneous data to improve data analysis and how can we choose amongst these methods? We categorize integrative methods for heterogeneous data analysis to Bayesian network based methods and multiple kernel based methods and describe them in detail with examples of successful applications in the bioinformatics field.
INDEX TERMS
Kernel, Bayes methods, Data integration, Data models, Bioinformatics, Proteins, Learning systems
CITATION

J. Thomas and L. Sael, "Overview of integrative analysis methods for heterogeneous data," 2015 International Conference on Big Data and Smart Computing (BigComp)(BIGCOMP), Jeju, South Korea, 2015, pp. 266-270.
doi:10.1109/35021BIGCOMP.2015.7072811
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