A comparison of graph- and kernel-based –omics data integration algorithms for classifying complex traits
Abstract Background High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-12-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1982-4 |