Machine Learning and Integrative Analysis of Biomedical Big Data

Machine Learning and Integrative Analysis of Biomedical Big Data

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical an...

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Bibliographic Details
Main Authors: Bilal Mirza, Wei Wang, Jie Wang, Howard Choi, Neo Christopher Chung, Peipei Ping
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Genes
Subjects:
machine learning
multi-omics
data integration
curse of dimensionality
heterogeneous data
missing data
class imbalance
scalability
Online Access:https://www.mdpi.com/2073-4425/10/2/87

Internet

https://www.mdpi.com/2073-4425/10/2/87

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